We recently sat down with several supply chain experts to identify the trends impacting global supply chains and what to expect going forward. KPMG Partner Peter Liddell weighed in on everything from the continuous disruption caused by materials shortages and geopolitical conflict to best practices for adapting to these challenges.
In January 1983 the computing world changed forever: Lotus 1-2-3 was released. This early spreadsheet program for IBM PCs ushered in the modern business computing environment by providing business users with a way to take ownership of their own solutions. Instead of relying on the IT department, users could use 1-2-3 to build applications by themselves, ushering in the era of end-user computing (EUC). Fast forward to today, and end-user computing is as popular as ever.
Ancient Greek mathematician Archimedes once said, “Give me a lever long enough and a fulcrum on which to place it, and I shall move the world.” He was right. When you intelligently use the right tools, you can move worlds and accomplish what on the surface seems impossible. Right now, developers are doing the impossible—building applications in record time that truly transform industries, improve business processes, and unlock radical productivity.
Leaders are taking a closer look at bank stress testing in the wake of recent bank failures. The significant impact of these collapses on the financial system, along with the government's extensive measures to prevent additional bank failures, is increasing the sense of urgency around enhanced regulatory supervision.
The first quarter of 2023 was quite a rollercoaster ride for the banking industry, marked by not one but two of the largest bank failures in U.S. history. As a result, regional banks took a hit as well, losing nearly $200 billion in deposits in just one week, according to the Federal Reserve. Because regional and smaller banks in the U.S. make up over a third of total bank lending, any pullback in credit provisioning could undermine financial stability and growth. The bottom line?
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.
