CPI – Center for Process Intelligence

Services

Our sercices are always tailored to your specified needs. However, to give an overview on our service portfolio, six major service areas are described below.

Data Extraction

Our understanding:

Extraction

  • identify data sources
  • identify data types
  • validate data

Transformation

  • aggregate data w.r.t. certain characteristics
  • improve data quality (up-on export)
  • structure data (on creation, “on saving”, on extraction)
  • anonymization of critical attributes

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  • data ready to use in target application
  • goal: (automated) data extraction process
     

Questions to be answered:

  • What kind of data is needed to solve my problem/ challenge?
  • How should my data be structured (data warehouse)?
  • What is the kind of questions I may answer w.r.t. to available data?
  • How can I improve data quality and availability?

Advanced Process & Data Analytics

Our understanding:

  • analyze process environment (involved resources, locations, time periods, starting events/activities, (desired) end events/activities)
  • analyze process hierarchy
  • analyze process conformance (deviations, rework)
  • analyze process performance (bottlenecks, ambiguous activities, activity orderings, time and cost perspectives)
  • analyze potential predictors for decision support
  • analyze automation potential
  • analyze (digital) process maturity
     

Questions to be answered:

  • Why a certain course of events or deviation happened (root cause analysis)
  • When this is likely to happen (prediction)
  • How you are able to prevent it (decision support/ making)

Process Modelling

Our understanding:

  • digital modelling of (executable) as-is processes based on process analysis
  • digital modelling of (executable) to-be process based on expert interviews, domain knowledge
  • create formally correct process models to apply conformance or performance analysis
  • scenario analysis based on executable process models
     

Questions to be answered:

  • How do my running processes actually look like?
  • Where should redesign efforts be made?
  • What, on a quantitative basis, are potential improvements in our process when redesigning it? (scenario based analysis)

Process Optimization

Our understanding:

  • digital adaption and transformation of existing workflows or processes to improve process performance and transparency
  • transform current processes and organisation
  • implement (identified) process automation approaches (RPA)
  • reduce process complexity
     

Questions to be answered:

  • How are we able to digitalize our current process environment?
  • What are our benefits when digitalizing processes?
  • How to motivate (organizational) transformation?

Process Monitoring

Our understanding:

  • recurrent analysis of process execution based on a desired to-be process (model)
  • employees have the knowledge needed to continuously monitor and control the processes and realize short-term improvements
  • process health-check (we are the doctor)
     

Questions to be answered:

  • What benefits do we exploit by implementing process monitoring?
  • Is our company ready for process monitoring?

Expert Trainings

Our understanding:

  • Providing state-of-the-art knowledge in data & process science
  • Analytics training: What do we need to know when looking for problem specific answers? What additional qualifications are needed in process centric units? What additional knowledge is needed in data centric units?
  • Get the best out of existing Process Mining solutions: specific trainings to extract maximal knowledge
  • Find the best tool for the job: understand the suitability of different tools and match them to your requirements
     

Questions to be answered:

  • What does my current application landscape offer?
  • How do we optimize the use of existing tools?
  • How do we extend tools according to our needs?