Benefits Of Workflow Automation
Whenever a new wave of technology splashes onto the scene, managers face the same questions: Where do we start applying it first? Do we go after the “low-hanging fruit” that will produce quick wins and build the case for more ambitious projects? Or should we strategically focus, with no delay, on the applications that will give us a decisive edge over competitors?
Right now, with the arrival of a revolutionary set of technologies for automating knowledge work — artificial intelligence in particular — we see teams grappling with these questions at high levels in organizations.
Intelligent automation (the term commonly used for robotic process automation, machine learning, and artificial intelligence in organizations) brings unprecedented speed, accuracy, and pattern-recognition power to business processes that routinely call for deciphering information, from fielding customers’ questions to complying with government regulations to detecting fraud and cyberattacks. Because that describes so much of the activity of modern workplaces, the deliberations about where to start and how to proceed are different than with other technologies. The same old answers don’t apply.
But, what is workflow automation?
Workflow automation is an approach to making the flow of tasks, documents and information across work-related activities perform independently in accordance with defined business rules. When implemented, this type of automation should be a straightforward process that is executed on a regular basis to improve everyday productivity.
Criteria for deciding when to use workflow automation include the following:
The task is repetitive.
The task needs to be achieved accurately, without any chance of human error.
A series of simple tasks can be made more efficient when automated.
Workflow automation should make it easier for an organization to streamline its workflows and identify other areas that can be automated to increase efficiency. For example, some automated workflow tasks can be managing spreadsheets or emails.
The potential to boost performance in the typical company with these tools is both broad and deep. In one company we know, a team was assembled to survey all of its operations, find areas where people’s time was being consumed by repetitive information-processing work, and come back with candidate tasks for automation. The list stretched to hundreds of things a smart machine could do to leverage workers’ creativity, increase speed to decision, improve accuracy, or enhance service to customers.
There are also strong competitive incentives: Because of this potential, companies are investing in these tools at blistering rates — according to Gartner, intelligent automation is the fastest growing area of enterprise tech investment. The pandemic gave the toolkit a giant shove forward as companies suddenly had to find new ways to perform mission-critical processes.
Workflows should be automated whenever possible for numerous reasons, including faster operations and an increase in efficiency and accuracy. Other improvements include the following:
This emanates from increased task efficiency, allowing employees to work on other, non-automated tasks.
Cost savings. The savings are due to increased productivity.
Visibility. If workflow mapping is implemented, then automation processes should be more transparent, giving an organization a top-down view of its workflows.
Communication improvements. If visibility is increased, then communication for employees can be more accurate.
Better customer service. This can be provided by automating responses to customer complaints, for example.
Potential to increase customer engagement. Customers might respond quicker using automation tools.
This can be improved because of an increased and mapped-out visibility of workflows.
Ridding redundancies. Workflow redundancies -- any task that is unnecessary -- can be identified more readily.
Improved overall end product. Human error is taken out of the equation.
Digital workflow can be tracked. This allows an organization to review how well its business operates.
Benefits of workflow automation
Benefits of workflow automation include the following:
reduced workflow cycles;
less need for manual labor;
less need for manual handling of products;
more visibility;
more visibility means an easier time identifying operational bottlenecks;
improved customer satisfaction when focus is placed on customers;
overall employee satisfaction, which eliminates the need for potentially dull, repetitive tasks;
improvements in employee satisfaction via providing workflow analysis tools, which can include dashboards and key performance indicators (KPIs);
better internal and external communications;
more accountability for who is responsible for what in an organization resulting from each step in a business workflow being clearly assigned to one action;
providing employees time to manage other tasks;
increased production;
saved costs;
less potential for human error;
scalability, because workflow automations can be changed and added whenever needed; and
more efficient task management, with the inclusion of dashboards, calendars and other tools that can be made available through workflow automation software tools.
Workflow automation can be used in industries and departments such as in healthcare, legal, DevOps, finance, marketing, sales, IT and human resources (HR). Here’s an example to illustrate examples of workflow automation, at a construction equipment manufacturer, there are three tempting areas to automate.
One is the solution a vendor is offering: a chatbot tool that can be fairly simply implemented in the internal IT help desk with immediate impact on wait times and headcount.
A second possibility is in finance, where sales forecasting could be enhanced by predictive modeling boosted by AI pattern recognition.
The third idea is a big one: if the company could use intelligent automation to create a “connected equipment” environment on customer job sites, its business model could shift to new revenue streams from digital services such as monitoring and controlling machinery remotely.
If you’re going for a relatively easy implementation and fast ROI, the first option is a no-brainer. If instead you’re looking for big publicity for your organization’s bold new vision, the third one’s the ticket. You can set up a tiger team or separate organization and give it full license to disrupt the existing business.
But note that neither of those approaches really prepares the ground for intelligent automation to spread to other applications by the existing organization; they don’t make the people of your organization generally more interested, receptive, or able to apply intelligent technology elsewhere. In other words, as an organization, taking these routes doesn’t take you far up the learning curve, toward greater maturity with the technology.
This is what option two would do — in large part because it would demand that the company get its act together on data. Without a good enterprise data strategy, people in different parts of the organization lack common standards regarding what data needs to be gathered and how it should be organized, cleaned, and prepped for analysis. This is a foundational capability that the company will need to have in place to make headway in using machine learning at scale. From the standpoint of capability building, it is easy to see how progress on enterprise data would unlock, say, 10 other projects — which in turn can be prioritized by the further capabilities they could add. Our manufacturing company could lay out a roadmap showing how, five years later, it will not only be reaping the returns of the specific projects, but also be generally and profoundly more ready to take on truly transformative initiatives.
Fifty years ago, when the legendary Peter Drucker coined the term “knowledge workers,” he also recognized how their rise in the global economy would challenge organizations. “The most important contribution management needs to make in the twenty-first century,” he wrote, is “to increase the productivity of knowledge work.” Finally, in intelligent automation, a powerful toolkit exists for doing that — and the race is on. Avoid the mad dash that has your organization chasing possibilities but with no collective progress. Choose your spots wisely, and your investment in intelligent automation can be a capability-building journey.
