- This is not a technical course.
But it's important for the sake of context
that we recognize that the reason we're talking about
the skills to manage a digital operation
is because there is a lot of technology
in your organization today.
And adoption is only accelerating.
While there are many frameworks out there
that highlight the intelligent automation landscape,
I'll use one I've developed
for the sake of working with C-suites.
The way we approach highlighting
the digital operations landscape
is to follow the way that work is traditionally done.
As you can see on the Intelligent Automation Landscape,
work begins on the left when data is received.
The data can come in in many formats,
whether it's voice, emails,
scanned documents, or chat interfaces.
The extent to which the data is structured or unstructured
determines the type of technology used to interpret it.
Once you receive the data you need to do something with it.
Often it's an action or request
which might be delegated to individuals who do the work.
If the tasks at hand are routine, mundane, and transactional
you can use an array of different technologies
to digitize and automate them,
including macros, RPA, attended automation,
and virtual agents.
After that there are then developing levels of complexity
and intelligence that are able to process,
analyze, and learn from the activities
that are occurring in your organization.
So this technology landscape represents
the various capabilities that inspired teams
across your company, are probably looking at right now.
And it's this landscape that executives today
need to understand and manage in concert with the people,
processes, and technologies that are already in place.
Ultimately technology in the operational functions
of a business run the gamut.
From simple script based tools
to more complicated algorithms
that often rely on intense amounts of data,
in order to draw inference and propose predictions.
Now, as we all know, the world of business
likes a new hot trend.
And so the focus of our attention often shifts.
As of the last few years,
we've been excited about robotic process automation,
intelligent automation, and various forms of learning,
be they machine or deep.
I recommend that you and your leadership teams
take the time to get comfortable
with each of the components
in this chart of digital elements.
Understand which classes of technology
are digitizing incoming data,
processing tasks, creating inference and analytics
from which to support decisioning.
And managing and allocating work between your people
and your digital labor in this new world of work.
If you're interested in RPI I would
proudly suggest that you check out my course,
titled Introducing Product Process Automation.
It's 90 minutes well spent.
And if you're interested in the other components
of our digital operation, table of elements.
We'll share a list of other LinkedIn learning courses.
You should consider in your personal IAA curriculum,
including AI, machine learning, data science,
and business analysis.