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Two weeks ago, hundreds of SAP Signavio process experts and enthusiasts met onsite in Berlin at our yearly flagship event, the SAP Signavio Business Transformation Forum, where we unveiled our vision around process observability One of the critical elements to further achieve process observability is journey to process analytics, which provides the necessary experience context to our customers´ business transformations. 


Principles of process observability


In this eighth post of the journey to process analytics blog series, we will guide you through a new perspective on traditional process mining SAP Signavio is pioneering in the market: experience-driven process mining. 

 

Let´s start with an example 


At the SAP Signavio Business Transformation Forum in Berlin, I was lucky to host one of our coveted hands-on experience-driven process mining workshops with my colleagues manuelmeindl and fabioferrari.


We started with an example: TaylorGear Inc., a successful bike manufacturer with a booming business that fell into the experience gap trap, focusing too much on saving costs and having efficient operations and not enough on the customer experience side. With customer complaints on the rise, it was time to change their approach. They had already aligned process and experience objectives, modeled their customer journeys and their business processes but had no visibility on what was really happening. 


Integrating the data 


Step one: if this happens at your company, start where your problems lie, such as low customer experience scores, and areas in which business KPIs are hurting. You need to keep your finger on the pulse of your customers: launch a customer survey or add a feedback button directly on your website to gather feedback and experience data.  


 

At SAP Signavio, we offer our customers a broad set of enterprise connectivity options and accelerators, which help our customers reduce the time and effort spent in this initial phase when integrating and preparing experience and/or operational data. Check out here an example.


In our workshop, we asked our participants to fill in a Qualtrics survey. Then, we showed them how this data could be integrated into SAP Signavio Process Intelligence, our end-to-end process mining solution. 


Tip: Beware of long lead times within your organization for approvals. One-time extracts, exclusion of data, or hashing can be an alternative for getting your approvals faster. 


 

Mapping the data 


As processes cause experiences, knowing where they intersect is essential, considering all touchpoints customers have with processes in an organization.

Thanks to SAP Signavio Journey Modeler, we had previously designed the customer journeys for our example bike company. We then mapped each journey step to the underlying processes, achieving a consistent view of the journey with a process perspective and integrated customer survey data from Qualtrics. 


SAP Signavio Journey Modeler - including the process perspective and data-driven insights from customer satisfaction data


Participants could now identify that some customers seemed unhappy in the bike configuration and delivery journey steps. Now the question was: how to link to the operations to see the root causes? 

After integrating the operational data of every process step from the corresponding systems, and modeling it with the respective tables and fields, a mapping of the process to the experience data was necessary. Different levels are possible to do the mapping (for both numerical or free text data from customer surveys):

  • per event or journey phase

  • per case

  • per cadence (e.g. once a year)

  • or as a one-off. 


 

Finding experience-driven process mining insights 


The exciting part: once data was in and mapped, workshop participants could start with the visualization and analysis to start finding insights into how and when processes were hurting the experience, and better understand the interactions between stakeholders with SAP Signavio Process Intelligence. 

Some examples: 

  • Widgets: Visualizations combining experience and operational data helped easily identify that customers of bikes manufactured in one of the manufacturing plants were unhappier.

  • Metric overlay in process discovery: By overlaying operational and experience metrics in process discovery for the affected plant, it was easy to identify that certain process steps at that plant led to lower experience metrics. Comparative process discovery helped confirm this with data from other plants. 

  • Variants by NPS or CSAT scores: By using process variant analysis ranked by experience scores, it was clear that some process variants for the plant led to lower customer satisfaction scores than others. 

  • Correlations or anomalies: Participants used the automated insights feature (which we launched earlier this year) to quickly discover hidden correlations or anomalies in the experience and operational data, such as a negative correlation between cycle times and customer satisfaction for specific suppliers. This helped us identify a potential remediation to Taylor Gear´s problem! 



SAP Signavio Process Intelligence - Process mining merging process and experience data. Widgets, correlations, and more help users achieve a holistic view on the process and experience layers


 

Sharing insights in the organization  


At SAP Signavio, we help our customers democratize process mining insights by making them easily consumable to take action. For instance, our workshop participants learnt how to embed metrics, widgets and more in the visualized customer journeys in SAP Signavio Journey Modeler. 

Sharing the insights with business users can help answer the question “our customer satisfaction is low at this journey step, and the reason, according to our process mining analysis, seems to be X. Now, what do we do to solve it?”  

A transformation journey can now start. Key stakeholders have a clear role and have an action plan to transform the process and the customer experience. 


  

Vision and next steps 


SAP Signavio journey to process analytics is here to stay. There is a common understanding in the market that a successful business transformation needs to factor in the perspective of customers, employees, suppliers, or other stakeholders. 

We are currently working on the next level of process mining and journey to process analytics with our innovation teams and partners. We are looking into NLP techniques to make sense of free texts and convert them into labels or attributes, automated clustering of process variants to match with journeys, decomposing experience values for more advanced matching and correlations, or outcome prediction... watch this space! 

 

Key takeaways



  1. Process mining initiatives often focus too much on saving costs and having efficient operations and not enough on the experience side. Mind the experience gap!

  2. Experience-driven process mining is a new perspective on traditional process mining. Process mining helps you achieve process observability, and adding the experience layer adds a new vector to achieve it and close that experience gap.

  3. Your receipt for success: Keep the finger on the pulse of your customers, consider their journeys, map journeys to your processes, and discover your combined process and experience reality with experience-driven process mining

  4. Sharing the insights with the organization is core to adapt fast and with confidence.

  5. SAP Signavio is already working on the next level of process mining and journey to process analytics... Keep watching this space!


 

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We´ll continue this series with a new topic, covering the rollout of process changes in your organization. Stay tuned! 

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