Robotic Process Automation (RPA)
The world is changing at an accelerating pace, and with 2019 almost in the rearview mirror, our strategy team takes a step back and tries to peer into the future. We explore the trends taking shape in the intelligent automation (IA) market and look for macro patterns that could give us a hint as to what’s to come in the year ahead. Here are our top 10 predictions that will impact the intelligent automation market over the next 12 months.
Continuing with business as usual—you know that isn’t going to get your organization where it needs to be and where you want it to be. And whether your goal for digital transformation is saving time and money, expanding operations or just delivering better service to customers (or all of these), you risk falling short if you miss the forest for the trees.
For years, T&L providers were trapped under the weight of manual business processes. In fact, one study found that 3 out of 4 logistics providers have not automated key customer-facing processes like scheduling shipments, monitoring changes and updating customer statuses.
While robotic process automation (RPA) is at the heart of many digital transformation efforts, it’s all too common for organizations to roll out their software robots in a piecemeal manner. For example, a company’s accounting department deploys a robot to automate invoice processing, while operations rolls out another to expedite shipping requests, without coordination between the departments. This decentralized approach presents a risk – one that leads to problems later.
Purchasing an RPA solution is like the Christmas present you can’t wait to open. The thought of automating tasks and processes is an exciting one and you can’t wait to get started. You might only use one robot from your RPA solution, choosing a specific test case to show ROI to management. With your test case completed and management asking how we roll this out enterprise-wide, here comes the challenge.
True digital automation requires more than just RPA. Customers need complementary technologies to automate the entire process journey – from content capture and data injection, to process orchestration, to advanced analytics informing business decisions. RPA is not the end-game; it’s just a piece in the intelligent automation puzzle.