What can process automation do for your organization and how does it differ from other types of automation? This primer will get you up to speed on process automation essentials and explain the basics of this important tech trend to help you get started.
“Data is knowledge, knowledge is power, and bad data equals bad decisions,” says Appian Senior Solutions Consultant Ben Crawley. We’ve all felt the sting of poorly integrated solutions, hard-to-access information, and sometimes, inaccurate data. This “bad data” is often the result of information that’s spread across different systems, creating data accuracy challenges and preventing you from having a single source of truth for your organization's information.
Think about a time when insufficient information or inaccessible data slowed you down from completing an assignment. Or maybe a time when your work required a lot of manual data entry that caused human error and rework, taking time away from higher value tasks. These moments of process frustration and inefficiency are exactly what workflow optimization can help with. Workflow optimization describes the strategies and measures taken to improve the flow of tasks and make processes more efficient.
If you think workflow orchestration sounds like tech jargon, check out this simple explanation and consider practical advice for how to apply it to your business processes. Let’s start with the basics: what is workflow orchestration? Put simply, workflow orchestration is the end-to-end management of people, digital workers, systems, and data in a process.
Process mining is a trusted tool for continuous improvement. It helps you understand your business processes as they actually are, shows you all of the variants and deviations, and provides suggested explanations for why process problems are occurring. Knowing how process mining works is one thing—putting it into practice is another. How do you know what makes a process a good candidate for mining? And how can you build a business case that a process needs to be mined?
Artificial intelligence (AI) has reached a tipping point in the public consciousness. Much of this has been driven by technology developments related to large language models (LLMs) and the release of generative AI tools, including ChatGPT from OpenAI. However, for enterprises shaping forward-looking AI strategy, a critical part of the conversation that needs to be addressed is the issue of private AI vs. public AI.
A great experience isn’t just about quality products and services or fast response rates. Users today expect all of that and more. They want easy, on-demand access to information and services from any device at any time. And they expect transitions across devices, locations, and processes to be seamless.
Your teams need constant connectivity to your organization's data and systems to operate effectively and thrive. And with digital transformation spurring a more rapid pace of innovation and technology adoption, this need for connected, democratized data is on the rise. That makes data silos an enemy you can no longer tolerate. Data fabric is the modern answer for eliminating data silos. Data silos occur when data is stored in separate systems or departments without proper integration.
In 2023, AI is everywhere, and not a day goes by without someone developing a new way to use tools like ChatGPT. With the increasing hype about the promise of AI, it’s more important than ever to cut through the noise and focus on how AI can help you deliver real business value. Modern process automation platforms go above and beyond the capabilities of AI alone.
April showers bring May feature releases to the Appian Platform. Get ready for sunny skies ahead with some seriously great new updates to Appian in 23.2. View documentation, release notes, discussion board posts, and tutorials on Community. The AI buzz is everywhere. If you’ve been getting bombarded with requests to “use more AI,” we’ve got you covered.
