Racing Toward Smarter Automation: The Evolution Of RPA

Biju Kewalram Biju Kewalram
May 25, 2020 AI & Machine Learning

Two ships carrying identical cargo dock at a busy port.

One shipment passes through slowly. There’s a mistake on a customs declaration form — a piece of cargo has the wrong safety certificate. And truck dispatchers are confused because some of the delivery addresses have been mistyped.

The other shipment passes through the port swiftly, without any hold-ups. Its documentation contains no errors.

Why? The second shipment has been managed with the help of robotic process automation (RPA).

The Promises Of Process Automation 

According to Digital Journal, RPA is “The use of software with artificial intelligence (AI) and machine learning capabilities to handle high-volume, repeatable tasks that previously required humans to perform.” These tasks might include maintenance of records and transactions, calculations and queries.

RPA offers impressive cost and efficiency savings as well as accuracy improvements, and while it doesn’t necessarily reduce a company’s headcount, it can free up employees to do more creative, interesting work that enhances company value.

RPA holds great promise for the logistics industry, in particular, which currently relies on vast amounts of paperwork and stacks of manually entered data to operate and conduct day-to-day shipping transactions. Generating and processing the right documents is time-consuming, monotonous work that is ripe for RPA disruption.

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RPA’s potential will fully emerge with the standardization of processes and as the underlying technology becomes more sophisticated through the use of cognitive or intelligent automation, which can handle unstructured as well as structured data. Employees no longer have to find information to feed into the system, largely removing the need for human intervention.

At our company, we’ve been piloting cognitive automation for several of our processes. One pilot, which has shown promising initial results, is automating the process of updating international arrivals and departures for air and ocean freight shipments. The RPA bot pulls a report and finds the shipments that should have arrived or departed and for which the information has not yet been updated. It then uses reference numbers to retrieve the related data and updates the operations systems with the shipment details.

Previously, much of this work would have been done manually by an operator. Unlike a human operator, though, the bot works 24/7 and can check constantly for updates. RPA significantly reduces the time that the manual process takes. It also implements strong process controls and completely accurate output — and all with far greater visibility for the end customer.

Here are some of the key learnings we can share from our own RPA journey so far.

Tips For Implementing RPA

• Develop a business case: Select your candidate for an RPA pilot carefully. Business processes that have high volumes and are very manual and repetitive are typically a good fit for RPA. You then need to split that problem into increments that you can address in two- to four-week sprints. An agile approach to development is a good way of quickly and efficiently testing how RPA could work in your organization.

• Decide what success looks like: Establishing clear measures of success early in the program will help you rally your resources and focus them sharply on the right outcomes. Some of the measures most consider for their program include rate of adoption (bot velocity), self-sufficiency (upskilling and providing certification of employees) and tangible business impact (service quality, scalability, compliance and productivity).

• Setting expectations: It can take years to achieve a high degree of standardization in an operating environment because businesses are constantly adapting to changing customer needs. It’s therefore critical to set a minimum threshold for standardization. This is usually in the range of 60% to 70%, which will allow you to adapt RPA to a dynamic operating environment while maximizing return on investment.

• Finding the right partner: Identifying the right partner is a key determinant for the long-term success of your RPA program. As you move to scale automation within your organization, access to a seasoned industry leader will provide invaluable insights and a strong ecosystem that can help you set up your program for success.

• Choose a user-friendly option: RPA tech is at its most powerful in the hands of a business user who really understands the processes. If you can choose “drag and drop” solutions that remove the technical aspects of programming and writing code, a business user is freed to focus on application and configuration.

• Get the team in place: Before committing to RPA, a business must think about the skills that will be required internally. If there’s a talent gap, think about how you can hire, train and streamline to get the best team possible.

• Capture and implement learnings: Pause and reflect on results from initial pilots, and feed these into an execution playbook for RPA. An execution playbook will help your organization develop an automation framework that is adapted to your operating environment and will help you scale your use of RPA in a sustainable way.

Reaping The Rewards

The new frontier of automation offers great promise. Cognitive automation can improve accuracy, enhance efficiency and free workers from the grind of monotonous manual tasks. But before you embark on your RPA journey, there are three key considerations: choosing the right partner, scaling an internal delivery organization and developing an execution playbook to do this sustainably.

If the trade and logistics industry can overcome its barriers to implementation — and especially the lack of industrywide standardized, automated processes — then the potential rewards are great. Cognitive automation has the potential to improve the customer experience by providing greater shipment visibility and smoother, faster shipping.

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