Consulting Data Analytics & Process Mining
We guide you to data-based decisions.
Services in the area of digitalization
Leistungen im Bereich Digitalisierung
How can ifp consulting support you with data analytics and process mining?
Data Analytics, Process Mining, Data Mining, Big Data
In a modern supply chain, numerous data is generated and stored. All machines generate process data and share their status. Products provide status and location messages, and logistics generates time stamps for goods postings and shipments.
Taken in isolation, only singular conclusions can be drawn from these data. The exponential increase in the amount of data (general rule: 90% of all data was created in the last two years) ensures that data is collected and stored faster than it is systematically used to make correct decisions. To gain far-reaching insights, the data must be linked and analyzed using novel methods and tools.
Data Analytics
Data analytics and process mining are increasingly used to transform complex data into valid information. We support you in the areas of data collection, data analysis and data interpretation.
ifp consulting has sophisticated tools to get more out of your data. The latest user knowledge from our innovation.lab as well as our many years of cross-industry experience in the SME environment make it enables us to gain:
- overarching contexts
- deep-rooted causes and
- future-proof findings
about your production, logistics, products, suppliers and customers.
Determine the position in the application field of digitalization
Determine the position in the application field of digitalization
Collect digital traces in IT systems
Find causes of deviation
Corporate processes are often confusing and complex.
Errors, inefficiencies or process loops can creep in, resulting in lost time, rising costs or loss of quality and ultimately dissatisfied customers. Process mining specifically involves collecting and storing process data based on digital traces in IT systems and translating it into a model of the real process.
In this way, undocumented process flows can be quickly documented and documented process flows can in turn be compared with reality. Process mining thus offers itself well as a data-driven alternative or complement to interviews, multi-moment surveys, and manual data analysis in consulting projects.
The results can now be used to optimize processes or train employees in the use of the documented processes. Unlike process KPIs, which may indicate that, for example, the optimal lead time has not been achieved and how high the deviation is, process mining can find and eliminate the cause of the deviation.
How does ifp consulting support consulting projects with big data analytics?
Big Data Analytics has established itself as a standard at ifp consulting in recent years and is used in more than 80% of all consulting projects.
- Data Analytics Strategy
Checking data quality, data availability and database homogeneity. Definition of the required evaluations and evaluation strategy - Data selection and extraction
Listing of the data required for the evaluations and support with extraction from the ERP system, with or without live data connection. - Data transformation
Data cleansing (correction or filtering of incorrect data) and data reduction (determination of the relevant aggregation level) - Data or process mining
Pattern recognition with big data software such as Power BI, Tableau, Celonis or in-house software - Interpretation & evaluation
based on more than 4,000 solutions already prepared for our customers.
Big Data Analytics Tools
Proven knowledge generation
The use of analysis tools is nowadays demanded by the customer in every second consultation. ifp consulting has been carrying out all projects involving the use of big data analysis tools for years, provided that the client’s data quality and structure allow it. The ifp consulting approach to big data analytics is based on tried-and-tested scientific knowledge generation processes.
What are the advantages of process mining?
A major advantage of process mining is objectivity. This is because process mining is based on data collected via IT systems and not on assumptions or subjective assessments by individuals.
In addition, process mining can be repeated regularly for individual processes, enabling iterative process optimization. This ensures agility in a rapidly changing corporate world. As with Big Data analyses, repeatability can be realized via a direct link to the ERP system.
Typical process mining use cases at ifp consulting are:
- Bottleneck analyses
- Lead time analysis and lead time reduction
- Identification and definition of the “Happy Path”
- Search for undesired deviations in the process and determine the causes
Your advantages when working with ifp consulting
- Systematic data analysis
Use of data analytics and process mining in all projects - Internal expertise
Consultant with data analytics specialization, mathematician and IT developer - ERP system data competence
In-depth knowledge of data structures. Support possibility during data preparation - Standardized tools
Use of widely used tools such as Tableau, Power BI, RapidMiner or Celonis - High adaptability
Use of customized applications and methods if required - Transparency
Provision of all source files and evaluations in the original format
What are the key success factors for data analytics and process mining?
You need the right methods and tools for big data analysis. Our team helps you analyze complex process and product data.
Evaluations
Key Takeaways
After the interpretation and evaluation of your data, new supplementary evaluations are prepared if necessary or existing evaluations are optimized.
These can be, for example:
- Automatic capacity planning based on raw SAP data and sales forecasts
- Cluster analyses, parts list analysis & optimization
- Make-or-Buy Analysis
- Master data cleansing and preparation
