Data Analytics &
We can help you make a data-based decision.
ifp Data and
Data Analytics, Process Mining, Data Mining, Big Data
Modern supply chains generate and store a large amount of data. All machines generate process data and report their status. For example, products provide status and location reports, and logistics generate timestamps for goods bookings and transports.
Taken alone, only singular conclusions can be drawn from this data. The exponential increase in the amount of data (rule of thumb: 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 extensive knowledge, the data must be linked with one another and evaluated using novel methods and tools.
Data analytics and process mining are used more and more often to convert complex data into valid information. The analysis and implementation phases can be accelerated by a factor of two or three. ifp consulting supports you in the field 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-sector experience in medium-sized companies, enable us:
Deep-seated causes and
to win over your production, logistics, products, suppliers and customers.
We support you with big data analytics
Big Data Analytics has established itself as the standard at ifp consulting in recent years and is used in more than 80% of all consulting projects.
- Check of data quality, data availability and database homogeneity. Definition of the necessary evaluations and evaluation strategy
- Data selection and extraction
- List of the data necessary for the evaluations and support with the 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 Tableau, Celonis or in-house software
- Interpretation & evaluation
- Based on 4,000 prepared solutions for our customers.
Analyze process data
Big Data Analysetools
Proven knowledge generation
Nowadays, the use of analysis tools is required by the customer for every second consultation. ifp consulting has been carrying out all projects with the use of big data analysis tools for years, provided the customer data quality and structure allow it. The ifp approach to Big Data Analytics is based on tried and tested scientific knowledge generation processes.
What are the advantages of process mining?
A great advantage of process mining is its objectivity – since process mining is based on data collected via IT systems and not on assumptions or subjective assessments of individual people.
In addition, process mining can be repeated regularly for individual processes so that iterative process optimization is possible. This ensures agility in a rapidly changing corporate world. As with big data analyzes, repeatability can be achieved via a direct connection to the ERP system.
Typical process mining applications at ifp consulting are:
- Bottleneck analyzes
- Lead time analysis and lead time reduction
- Determination and definition of the “happy path”
- Search for undesirable deviations in the process and determine the causes
Cooperation with ifp consulting
Systematic data analytics
Standard use of data analytics and process mining in all projects
Consultant with data analytics specialization, mathematician and IT developer
ERP system data literacy
In-depth knowledge of data structures. Possibility of support with data preparation
Use of widely used tools such as Tableau, Power BI, RapidMiner or Celonis
Use of custom applications and methods when needed
Provision of all source files and evaluations in the original format
Factors of success
You need the right methods and tools for big data analysis. Our team will help you analyze complex process and product data.
After your data has been interpreted and evaluated, new additional evaluations may be prepared or existing evaluations optimized.
These can be, for example:
- Automatic capacity planning based on raw SAP data and sales forecasts
- Cluster analyzes BOM analysis and optimization
- Make-or-buy analyzes
- Master data cleansing and preparation