Process Mining and O2C in Power BI
Ensuring that you have an automated seamless and optimized O2C process will have a contagion effect on the rest of your busines. The internal controls must be analyzed with process mining to identify areas for improvement. Bottleneck, delays, incorrect invoicing, and the like in one area of the O2C process can cause disastrous backups in another and at the end of the day cost the company time, money and ultimately, customers. Because the full O2P process is a complex relationship between departments, getting these departments on the right journey is paramount.
If systems are not fluid, complaints will range from shipping delays to delivery of the wrong item. If this happens frequently enough the business will be paying out business errors to fix the problem and repair the customer relationship.
To keep customers happy and become long time loyal purchasers – you need a flawless end to end process and customer journey.
Increase your process efficiency with Microsoft Power BI and PAFnow for ‘Order to Cash’.
Join Daniel Hughes and Robert Connolly as we simplify the complex topic of this end-to-end business processes and how Microsoft Power BI and PAFnow can optimize O2C.
Learn how to remedy some of the following paint points:
- Varying payment methods and terms
- Late product or service deliveries
- Credit blocks which effects working capital
- Too many customer touch points
- Low compliance to agreed delivery date
- Complex generation of shipping documents
- Late invoicing
Process Mining - What is it all about?
Prepare yourself for the webinar. Watch this 2-minute video to see how easy and convenient Process Mining really is.
Daniel Hughes has 20 years of experience helping companies select enterprise software technologies. He focuses on helping companies overcome process challenges by applying cutting edge technology to the problem. His background includes software companies focused on BI & analytics, AI & ML, BPM & workflow, intelligent automation, and most recently Process Mining. He has helped companies dissect and automate processes from procure to pay, to mortgage origination, to hire to retire, and customer journey. Daniel earned a degree in Information Systems from Baylor University.
Robert Connolly is a graduate from the University of Michigan: College of Engineering where he earned his degree in Computer Science. At PAF he works as a Data Analyst for the US team in Ann Arbor, MI. He believes that business intelligence and analytics have the potential to change the world and how every business operates. He aims to bring business intelligence to customers worldwide to make sure every business has the opportunity for clarity in their data and efficiency with analysis.