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Lufthansa Cargo delivers end-to-end process visibility, improves customer experience

Lufthansa Cargo, a leading air freight company that covers about 300 destinations in more than 100 countries, has transformed its operations by optimizing end-to-end processes across the company's major business domains.

To deliver an end-to-end process, Lufthansa Cargo used a business object called the Air Waybill (AWB) that features a central data model and connects Customer Booking, Handling, Customer Service to Revenue Accounting. The AWB, which has an identification number that is unique to every shipment, is the document created by or on the behalf of the shipper and represents the contract between the shipper and carrier to transport goods.

Lufthansa Cargo's efforts are an early foray into Object Centric Process Mining (OCPM), which is the base technology for Celonis Process Sphere. The AWB sits at the core of Lufthansa Cargo's 7.2 billion freight ton kilometers delivered in 2022.

"We didn't want to look into a specific area or process," said Michele D’Angelo, Senior Manager Processes and Performance for Global Customer Service at Lufthansa Cargo. "We wanted to cover the real end-to-end process. We are talking about various interfaces we connected to Celonis to cover that whole journey from a process perspective."

Key performance indicators for the AWB included cost efficiency, process compliance and quality. The Global Customer Service team also looked at throughput time, reduction of customer claims and irregularities. “Key metrics for Finance and Accounting were data quality as well as quality in a specific time frame - especially for billing and reporting purposes,” said Birgit Schüller, Senior Manager Provider/Process Management for Accounting.

The project

Boiling down an end-to-end process into one business object such as the AWB masks a lot of complexity underneath. The AWB project was driven by two Lufthansa Cargo functions, Finance and Controlling and Global Fulfillment Management, and then expanded.

According to Lufthansa Cargo’s Process Mining Team, the AWB implementation took 9 months with time split evenly between data integration and analytics creation.

The data model behind AWB is fed by nine different interfaces filling more than 60 tables in the data model. Tracking more than 70 different events for one AWB case, Lufthansa Cargo can capture about 2 million AWB records representing more than 80 million activities.

Primary systems include booking and handling via iCargo by IBS, customer service with Microsoft Dynamics 365 and revenue accounting by Lufthansa Industry Solutions.

The project looked to provide transparency for further optimization. Pain points included:

While Lufthansa Cargo had data in multiple systems, it lacked end-to-end process transparency.

The Revenue Accounting process lacked transparency for data and process dependencies between its systems and Booking and Handling.

Lufthansa Cargo lacked a systematic feedback loop between Customer Service and core processes in Handling. Without a feedback loop, Lufthansa Cargo struggled to identify and eliminate root causes for irregularities.

The company's goal was to foster cross-divisional data exchange and transparency, visualize results from one single source of the truth and find root causes and fix them with automated actions.

D’Angelo said the transparency helped all stakeholders to collaborate better. "In the past, all of the processes and IT systems behind the processes were siloed. The data was captured for each individual department and process owner," he said. "Once we consolidated all the data into a single data model as one unified data source, we could start connecting the dots and getting the people to sit at one table. The collaboration is much more effective."

Indeed, Lufthansa Cargo's AWB project has more than 400 registered users.

Enhancing end-to-end process transparency

Lufthansa Cargo implemented Celonis as its Process Mining tool for end-to-end transparency for all AWB-related processes. Finance and Controlling and Global Fulfillment Management developed a joint approach that included Sales, Handling and Customer Service to Revenue Accounting along with the company's information technology team.

The company started with a minimum viable product approach and scaled to connect an increasing number of Lufthansa Cargo's interfaces.

In addition, Finance and Accounting already was using Celonis Action Engine Notifications to support processes and intercept unusual values.

“When we introduced Process Mining in the finance department, our goal was to gain end-to-end transparency and identify areas of action to optimize our revenue accounting processes. We have succeeded in implementing various measures that significantly reduced manual workload in our teams. With the newly created dashboards we monitor the corrections in revenue accounting and what I personally really enjoy and appreciate is the fact that we have data from many systems in one place and the application is easy to use. I look forward to integrating further data sources into Celonis and thus using the power of Process Mining to simplify our processes, make them more efficient and last but not least – save costs”, says Katarzyna Naganuma, Senior Director of Finance, Accounting, and Taxes.

Solving for process transparency also requires a heavy dose of data integration. Patrick Lührs, Application Manager Data Analytics at Lufthansa Cargo, explained:

Since our data is generated across several systems - of which only some provide long-term storage, and the detailed information that we intended to mine for our purposes is not stored in a central ERP system like SAP, we used our company data lake as an “in-between” layer for data storage that we can always go back to and integrate more from if we need to have an even deeper look at a certain interface inside Celonis.

Lührs said the approach enabled Lufthansa Cargo to ingest more data upfront that then could be narrowed down to what was needed for analysis in Celonis. “While the structure of the different datasets involved was diverse, we found it very useful to define as few patterns for processing as possible, allowing for easier maintenance and extension of our data processing pipelines,” he said. “At the end of that process, Celonis allowed us to generate an integrated view of often disjunct datasets from different systems across multiple business subprocesses.”

D’Angelo said the end-to-end business process view provides Lufthansa Cargo with new perspectives from other departments on the same issue. He said:

For the first time, data has brought people together and compelled them to collaborate. In our case, colleagues from different departments with different perspectives can contribute their experiences and interpret results. Data analysis is one thing, but complex processes in a highly regulated industry requires expertise in interpretation. Therefore, it is a perfect match to use data and technology to establish a classical Plan-Do-Check-Act cycle in an environment that is not siloed anymore.

With new perspectives, D’Angelo said Lufthansa Cargo has been able to improve performance indicators such as handling times for customer incidents or compensations, which were previously treated separately. By identifying process variations in the customer value data stream, Lufthansa Cargo has been able to fix problems before the customer is impacted. “Now a new data model can also be established in no time that considers your customer rather than an AWB number,” he said.

Through Celonis and the implementation of process mining, we have increased transparency of our shipment process, improving our ability to identify and address any irregularities. The end-to-end process optimization has fostered collaboration and communication between different teams and enables a holistic evaluation. We are now able to identify the biggest levers to improve the customer experience across various touchpoints, i.e., by steering our customer service performance and providing better solutions to the customer in less time.

Our partnership with Celonis supports us in constantly improving customer service at Lufthansa Cargo," says Jule Parulewski, Senior Director Global Customer Service.

What's next?

Lufthansa Cargo plans to take a top-down approach and create a cross-functional learning organization to close the customer service feedback loop and use sentiment analysis to gain more insights to improve product and services.

Finance and Accounting plans to implement three more AWB business object Revenue Accounting processes and one new object related process in Celonis.

Lufthansa Cargo is also looking to use near-time data to act on short-term supply chain issues. The company is looking to create more compact data models to minimize loading times.

Finally, Lufthansa Cargo is looking to create more business objects to expand into more processes.

As Lufthansa Cargo scales its process mining approach it will benefit from lessons learned. D’Angelo and the Process Mining colleagues provided the following tips for other Celonis customers on the process transparency journey. Here’s a look:

Technical advice:

  • Be aware of the size of the data model and time it takes to load data as well as the time it takes to run analysis.

  • Break one big model down to several smaller ones to get near real-time data faster for live operational use cases.

  • Watch storage costs.

  • In case of the intention to use Celonis as an internal control system clarify with your auditors first the preconditions regarding your individual technical setup. Perhaps a certification like ISAE 3402 is needed.

Organizational best practices:

  • Know that new technologies also require a new way of thinking as well as new roles and responsibilities.

  • Focus on change management as you switch from project management to daily operation mode.

  • Find new use cases focused on value via a Center of Excellence (CoE).

  • Invest sufficient effort to bring a CoE on corporate level alive.

  • Find the right people with the right skill and mind-set.

  • Build a user-community and ensure knowledge sharing.

Larry Dignan mugshot 2022
Larry Dignan
Editor in Chief (former)

Larry Dignan is the former Editor in Chief of Celonis Media. Before joining Celonis, he was Editor in Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in, Inter@ctive Week, The New York Times, and Financial Planning magazine.

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