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Workflow Automation with a Human Touch

Workflow Automation with a Human Touch

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Workflow Automation with a Human Touch
Posted: Thursday, November 12, 2015

In a recent survey we asked a handful of leading media facilities in Europe and North America, among other things, to what extent they agreed with the following two statements:

  1. There are too many manual steps in my workflow
  2. There is potential to reduce the number of manual steps through workflow automation

Although there was a little variation between the European and American answers, the trends were largely similar, and the combined result is shown below for the first time.

It is clear that while the majority of those surveyed agree that there is potential to reduce the number of manual steps in their workflow, the picture of whether they should or not is less clear. However, in conversation following the survey with the respondents, those who were not strongly in agreement that there were too many manual steps in the workflow could be placed into one or even all of the following schools of thought:

“Workflow automation is so complex & costly that it’s easier/quicker/cheaper just to continue with manual steps.”

Well, they needn’t be. While many legacy media processing platforms and workflow automation products use convoluted proprietary methods to describe, define, develop and implement workflows, the Dalet AmberFin Workflow Engine uses the standardized and widely deployed BPMN 2.0 specification to visualize, document and deploy workflows. Let’s take the example of the simple “normalize and store” workflow below, where incoming assets are transformed into the house format, in this case AS-11 UK-DPP files (both HD and SD), QC’d and sent to the archive.

Not only is the diagrammatic description of the workflow incredibly easy to read, understand and modify, it is a standardized graphical representation of an XML description of the workflow that can be very easily deployed, saved and shared. The workflow is built from neatly contained tasks that are presented to the user in a “stencil” set that can be easily dragged into the workflow area and intuitively connected together. Specially created or modified tasks can also be easily saved back to the stencil set for future use. Saved workflows are identified not just by name but by a version number to enable workflows to evolve while avoiding regression issues.

Once deployed, the AmberFin Workflow Engine further aids administration of workflows by providing visual tracking and advanced logging for each instance of a workflow, enabling any issues to by identified and resolved quickly and efficiently.

“Manual steps are required to ensure quality output.”

Perhaps in this case we were asking the wrong question, or at least, not being clear to differentiate between “manual steps” and a “user task.” Automated file-based QC systems have come a long way since they were first introduced to the market, and AmberFin UQC (Unified Quality Control) integrates the best of them – Venera Pulsar, Interra Baton, VidCheck VidChecker and Tektronix Aurora – but particularly in cases where an asset fails automated QC, there is no substitute for human judgment.

In the example above, you can see how the Workflow Engine can be very easily configured to send a notification and/or create a user task to trigger a human review of the material via the AmberFin player and UQC timeline – presenting all the available QC data to the user in an intuitive timeline view. Users can easily qualify or disregard the results from the automated QC tool, adding annotation and mark up where necessary and, on completion of review, end the user task with the Workflow Engine continuing to automate the remainder of the workflow.

Workflow automation need not be complex or costly, and automation with the “human touch” can provide true “best of breed” media processing operations. To find out how Dalet AmberFin and the Workflow Engine can help simplify and improve your media processing and transformation, click here to request a demo.

Posted by Ben Davenport

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