If the last few months have taught us anything, it’s that we need to be prepared to pivot our business strategies and processes on a dime. As COVID-19 forced offices to close and entire industries to halt business, we learned just how important it was for organizations to be ready to try something different.
But in order for the change to be successful (especially in times of such massive uncertainty), it needs to be rooted in real-world trends. This is where understanding the data behind your processes is important.
With the Hackett Group predicting finance budgets will shrink by up to 3.4% this year, it’s even more important to find cost-efficient solutions that not only streamline processes but also allow organizations to make the most of the data they have. One way to do this is by leveraging new technologies and modernizing finance applications platforms, including trading process mapping for process mining.
Process mining allows you and your stakeholders to understand the key drivers of rework, bottlenecks, inefficiency and lost time in your processes. By capturing event log data from your source systems, you're able to identify friction points in real time and get to the root cause of inefficiencies quickly.
Where process mapping only scratched the surface, process mining provides deep insights into the key drivers of inefficiencies, bottlenecks, and time lost due to ineffective or inefficient processes. Process mining looks at all levels of a company’s processes at once, identifying areas of improvement using data-driven, automated discovery that reduces time spent scoping out high-friction areas and hidden processes.
For finance departments, outing these inefficiencies provides an opportunity to create more cost-effective operations, improving the speed and quality of deliveries and creating a better stakeholder experience—all while keeping data secure.
The finance and accounting landscape often involves multiple technologies that can lead to a number of complications, including complex functions, inconsistencies across geographies and decentralized lines of business, and incomplete and inaccurate process documentation. These technological complications in turn create process complications.
Advances in process mining technology now enable real-time execution management. With this technology in place, cases that cannot be handled by straight-through processing (STP) workflows can now trigger real-time automated recommendations and actions.
For example, the benefit of cash discounts may not be maximized due to delays in goods receipt postings. In this case, by leveraging process mining to support execution management, every invoice can be automatically evaluated for these potential cash discount opportunities relative to the discount due date. The system can then make recommendations to payables associates, such as scheduling off-cycle payments runs that will capture significant discounts associated with the recently posted goods receipts that missed the scheduled payments run.
In another example, if cash discounts are not maximized due to unfavorable discrepancies between invoice and contract terms, process mining can evaluate every invoice and recommend that your AP department update the invoice with contract discount terms. These examples show that with process-mining execution management functionality, inefficiencies can be identified in real-time, with prioritized triggers and recommendations, and proactive remediation to drive business benefits.
When assessing processes manually, there is only so much time you can spend talking about what you can do better. Unfortunately, this means you’re often reviewing processes after weeks or months (or maybe even quarters) of running inefficiently.
The real-time data that process mining provides allows your team to act on them almost immediately. Rather than wasting time (and money) continuing to use processes that just don’t work, you can quickly implement changes that improve productivity and reduce costs. It's built to handle the real-world complexities and flux associated with the modern process environment. It elevates the conversation around your processes from individual parts of the business so you can focus on optimizing operations to benefit the entire organization.
Real-time data and predictive analytics also provide more reliable revenue forecasts and a better understanding of cash flows. During unpredictable times like the ones we’re facing now, being able to access up-to-date information about customer behavior can be a lifesaver.
Many companies look at automation as a magic bullet to achieving productivity. And while it certainly is a powerful tool, RPA bots are only as strong as the processes behind them. When processes are inefficient, so is your automation.
Implementing process mining before RPA provides an opportunity to clean up your processes before integrating advanced technologies. When processes work the way they should—without inefficiencies hiding in the background—bots can run more smoothly and with fewer complications.
By identifying and diagnosing the inefficiencies and friction points that are all too common in financial processes, process mining helps finance departments tack the laundry list of transformational expectations set out in front of them. Real-time advanced analytics and AI integration can give financial operations the ability to reduce complexity and drive efficiencies.
This article is from Cognizant, one of the world's leading professional services companies, transforming clients' business, operating and technology models for the digital era and a trusted Celonis partner. To learn more about Celonis' partner program, visit out Partner Page.
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