We support you in setting up a comprehensive live analysis
Analysis & optimization of your BI solution
- BI Tools
Selection and implementation of software suitable for your company
- Building KPI Trees
The right information in the right place from the shop floor to management
- Drill-down Dashboards
Get to the heart of the deviation with live interactive dashboards
- Key figure development
Systematic derivation of specific key figures
Internal know-how development through key user training
Track root causes with interactive dashboards
We assume that a drop in productivity has been identified in the SPQL dashboard below. For 2 scenarios, an example is given of how a source of error can be identified. Buttons and interactive diagrams are available for exploration – data basis are mainly ERP, MES & BDE systems – if necessary also monthly files from training systems, separate personnel systems, etc. stored on a server.
Scenario A – Raw material quality defects
In addition to the drop in productivity, we see directly in the SPQL dashboard that there were an unusually high number of Q messages at the same time. By clicking on the Q-messages, a new view opens and we see that a large part of the Q-message “Raw material defective” has been posted. Through the interactive dashboard, we can drill down one level. Here, for example are the materials and work centers responsible for Q-messages displayed in descending order of frequency – if the productivity analysis is performed with a filter on the work centers the same productivity as in the previous month has been achieved. The correlation is therefore clear. If necessary, measures must be taken with regard to the quality of the suppliers.
Scenario B – Overloaded workplace
In the SPQL dashboard, there are no explanations other than the productivity drop. We go into the productivity analysis at the job level and see some unproductive jobs. When switching the view to the backlog, a workstation is heavily overloaded. If we click on this, the job analysis shows us that the following jobs are the unproductive jobs. Now we know, for one thing, where short-term countermeasures need to attack – at the bottleneck. In contrast to scenario A, the disposition or a disorder seems to be the background here. With another dashboard showing the state distribution of jobs, we can disprove the thesis of disruption. Scenario B is therefore a special dispositive situation because of the short-term productivity slump.