By combining the strength of SAP’s in-memory platform with the revolutionary process mining technology of Celonis, Vodafone now is able to leverage its data to get full transparency about how processes are really executed.
Vodafone was looking for a way to understand how its corporate process models were executed in reality. In this way, it wanted to close the information gap and link KPIs to root causes. By combining the strength of SAP’s in-memory platform with the revolutionary process mining technology of Celonis, Vodafone now is able to leverage its data to get full transparency about how processes are really executed.
They've had great success – shortly after the introduction of process mining, improvement in business-critical back-end processes has become visible, and Vodafone expects much more to follow.
With 446 million customers, mobile operations in 26 countries and fixed broadband operations in 17 countries, Vodafone is one of the world’s largest telecommunications companies. Operating in the market for over 30 years, Vodafone understands that its customers need a communications partner with solutions that scale and adapt as their businesses change.
This means that back-end processes like purchase-to-pay, which also play a key role in driving business success and customer satisfaction, need to adapt. Simplifying these processes by making them faster and more flexible to meet customers’ needs is essential for Vodafone’s leadership in the market.
However – with hundreds of thousands of transactions accumulating an enormous amount of “deep Data" – Vodafone lacked the necessary insights into how processes were executed and performing in reality, especially compared to process models and documentations.
KPIs indicated that processes were not running smoothly, but it took too long to get to the root causes of process weaknesses. The gap between performance losses and determining the appropriate course of action to improve the situation was too wide. Precious time was lost, which had a particularly monetary impact on the time-dependent Purchase-to-Pay process.
A solution that could bring transparency to Vodafone’s processes and provide actionable insights into the root causes of problems was needed.
In order to build a bridge across the information gap, Vodafone introduced a game-changing solution: Celonis Process Mining. This technology leverages the benefits of Vodafone’s SAP S/4HANA infrastructure to make the company’s own “deep data” speak in a way that leads to actionable insights by:
Creating full transparency with a visualization of as-is processes in real time
Identifying all process variants and highlighting deviations
Uncovering bottlenecks, rework, delays, cost drivers and other inefficiencies
Assessing KPIs and other metrics by analyzing the root causes of process weaknesses
Exploring the full potential for further process optimization (e.g. standardization, process re-design, automation)
Providing actionable reports for operational process improvements
Being rapidly deployable and enterprise-ready
Being a cross-industry solution complementing the SAP landscape
Celonis Process Mining reconstructs and visualizes Vodafone’s as-is Purchase-to-Pay process end-to-end from digital traces in SAP systems. It shows the big picture and allows drill-downs at the same time which, in turn, reveals root causes for problems.
Like a visual search engine, it is possible to zoom into transactions, filter on any given KPIs and find out quickly where and why deviations and inefficiencies occur. In this way, process mining creates the optimal basis for further improving the efficiency and quality of a process.
Process Mining on SAP S/4HANA is changing the way people at Vodafone work. With simplification and transparency, they no longer have to adapt to rigid processes – they can design processes to fit their needs and become much more productive. If a process becomes inefficient, process mining enables businesses to spend less time on guessing and searching for the problem. Rather, process mining triggers the fact-based discussion of solutions and taking immediate counter measures for improving the situation.
Changes the perspective and works on improving “the real process”
Stop guessing and move from insights to action in no time
Get to know the “why” and make fact-based decisions with better impact
Save time and make better use of it with real-time analyses and monitoring
Increase productivity by shaping and automating processes
Enhance overall compliance
Celonis Process Mining solution on SAP S/4HANA has successfully been applied to Vodafone’s global purchase-to-pay process, creating transparency and standardizing it to run with significantly increased efficiency.
>820,000 purchase orders
>3.5M asset additions
Among others, the following analyses were carried out to improve processes:
Where and how does the as-is process deviate from the to-be (standard) process? Can it be further standardized and automated (Robotics)
Which processes could be automated further?
Where does automation fail, resulting in a lot of manual rework?
What is the impact of individual processes on the value chain, and how can we improve time to market?
Where are the bottlenecks in processes?
Which purchase orders and vendors have high rework ratios?
What are the most frequent rework activities (i.e. removal of payment blocks and declined purchase orders)?
How to improve 3-way matches (payment details on purchase orders, goods receipts and invoices)
Check compliance: Where and why were approval steps skipped?
Vodafone has been running SAP S/4HANA since 2013 – in the course of a major digital transformation strategy, it now draws its information from one global enterprise system. Process Mining is an extraordinary use case that leverages the full power of Vodafone’s S/4HANA infrastructure.
Celonis technology is tightly integrated into SAP S/4HANA via the Application Function Library (AFL) to leverage the full power of in-memory computing.
Since the Celonis Process Analytics Engine runs directly inside SAP S/4HANA, the performance of large datasets is significantly increased.