How can Manufacturing Companies Overcome RPA Adoption Challenges?

For decades, the manufacturing sector has used robotics throughout its assembly lines as well as supply chains. However, similar advances have been late to reach backend processes. Even today, manufacturing companies rely on outdated, manual processes to perform functions in accounts management, invoice processing, and compliance, which are tedious, error-prone, inefficient, and unscalable.

Robotic Process Automation (RPA) can change that, unlocking operational and cost efficiencies at scale. RPA is the process of deploying digital robots (also known as bots) to mimic human behavior. For instance, it is not uncommon for accounts teams to receive invoices in a Microsoft Excel format. Employees then process these invoices manually — typing information from the spreadsheet into the ERP system — before making payments. With RPA, a bot can take care of this speedily, without errors, and at scale.

While the advantages of RPA are plenty, manufacturing organizations also face significant challenges in adoption. In this blog post, we explore such challenges and what manufacturers can do to overcome them.

Lack of widespread digitization

Manufacturing companies still follow paper-based processes for various tasks such as contracts and invoicing, where they might be legally required to maintain a paper trail. There is a misconception that RPA is ineffective in such cases, where organizations don’t have picture-perfect digital processes. As a result, organizations are reluctant to adopt RPA.

This is, in fact, a missed opportunity. RPA can bridge the gap between paper-based processes and digital ones by bringing together computer vision, OCR technology, and bots.

Low technology maturity

Manufacturing organizations that haven’t gone through the phase of digital transformation might feel technologically unprepared for RPA. Without large information technology teams, they might feel ill-equipped to start an automation journey. Should we implement it on-prem or on the cloud? How do we integrate it with our existing systems? These are questions that often stop organizations from embracing RPA wholeheartedly.

In reality, RPA can easily integrate with legacy and modern systems, bridging the gap between the two. That said, RPA is often used to power large-scale digital transformation initiatives and data migration.

Non-standardized processes

Let’s take the example of vendor invoices we saw earlier. Manufacturing companies typically use hundreds, if not thousands, of vendors for raw materials. Each of them might submit their invoices in different formats, styles, frequencies, etc. The accounts teams typically process each manually. Given the amount of time and energy spent in these processes, organizations believe they are too complex to automate.

With RPA, the opposite is true. Firstly, most organizational processes have some standardization, which can be leveraged before automation. Moreover, RPA mimics human behavior — it can perform the same tasks humans perform, despite the input document being in disparate formats. An Intelligent Automation solution can learn with time and become autonomous even while following non-standardized processes.

Evolving compliance standards

The manufacturing industry is subject to several compliance restrictions. In sectors like automobile manufacturing, compliance is also constantly evolving. Each year, rules change, submissions increase. Manufacturers believe that it would be a huge challenge to train bots to adapt to these changes.

However, RPA can play a significant role in making compliance easier. Best RPA tools, such as AssistEdge, are easily updatable, enabling you to retrain bots as and when needed. RPA can help ensure organization-wide consistency of compliance, which is complex with manual processes.

Past failures

Several forward-thinking manufacturing organizations have tried RPA implementations in the past and failed. This could have been because of mismatched expectations, wrong RPA product, inappropriate use cases, sub-optimal infrastructure, and lack of leadership buy-in. Such failed experiments can not only be expensive but can also make companies reluctant to try again.

However, the cost savings and incremental value RPA can deliver for manufacturing companies can recover the loss of a failed implementation many times over.

In the post-COVID era, manufacturing organizations are under mounting pressures to reduce costs and improve efficiency to increase productivity. While the assembly line processes are already tightly optimized, back-office functions present an excellent opportunity to do this. It is here that RPA can play a significant role.

Learn how RPA can transform the manufacturing value chain — from procurement, logistics, supply and demand planning, order processing and service, production planning, to customer service. Read more.