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In business, speed is key. When facing rapid change, adapting slowly eats into an organization’s revenue, opportunities, and market share. This has led organizations to deploy business process automation technologies to streamline processes, roll out products faster, and deliver services of a higher quality. However, organizations often stitch together disparate automation tools, leading to disjointed IT ecosystems and bloated licensing costs.

Developing, distributing, and monitoring a drug or medical device is an extensive process. It involves the coordination of people, systems, and substantial amounts of data. Production slowdowns negatively impact the product lifecycle, adding unnecessary costs and keeping valuable products from the patients who need them. The need for automation is evident.

Think about a time when insufficient information or inaccessible data slowed you down. Or maybe a time when your work required manual data entry that resulted in human error and rework, taking time away from higher value tasks. These moments of process frustration and inefficiency are exactly what workflow optimization helps address. Workflow optimization describes the strategies and measures taken to improve the flow of daily tasks and make processes more efficient.

Workflow automation involves automating repetitive tasks and processes in a sequence using technology, reducing the need for manual intervention. It involves designing, creating, deploying, and automating business processes like data entry and customer interactions. Workflow automation uses software to replace manual and paper-based processes. Its primary goal is to ensure that the right people work on the right tasks at the right time.

In 24.2, we introduced our enterprise copilot. Enterprise copilot allows you to upload business documents and collect them in knowledge sets. From there, you can ask questions about information in these documents and receive answers quickly. For instance, an organization with a heavy regulatory burden could upload legislative and operational documents. Then, these employees could get insights from Appian AI Copilot to ensure they adhere to compliance requirements.

Ramkumar Nottath, the Senior Solutions Architect at AWS, beautifully puts it. And that’s where low-code or no-code ETL platforms can help—to make the data consumable and democratize it. In this blog, I explain low-code vs. no-code from my experience.

Your organization is likely sitting atop vast quantities of diverse data. However, all that data must undergo certain processes before you can fully leverage it. Data discovery is among those processes. Let’s learn more about it.

Workflows determine how organizations conduct processes. These workflows can initially be very straightforward—just a simple series of steps that must be completed sequentially to achieve a particular outcome. However, the steps can become more complicated as business processes and requirements become more extensive. Your organization needs to keep these workflows running smoothly even as they become more complicated.

Smooth and effective data migration helps organizations move data across systems efficiently to maintain their competitive advantage. Still, Gartner reports that only 17% of initiatives involving data migration are completed within their budgets or set timelines. Understanding these data migration challenges is the first step toward overcoming them. In this blog, we’ll explore data migration and its different types, challenges, and strategies for dealing with them.