Schunk Xycarb Technology

Role

Process Improvement / Data Analysis

Duration

6 months

Industry

Manufacturing

Power BI

Excel

SAP

Value Stream Mapping

Context

At Schunk Xycarb Technology (SXT), I worked for 6 months on accelerating and improving operations by translating machine and planning data into actionable insights and concrete improvements.

SXT is a manufacturing company where machine efficiency, planning, and customer communication are critical to operational success.

Challenge

There were three major challenges:

Limited transparency: How efficiently machines ran daily and where bottlenecks occurred was unclear
Staff Planning: Staff planning did not align well with available workplaces/machines, leading to moments of over- or understaffing
Unreliable SAP processing times: Processing times in SAP were often incorrect, making planning and customer communication unnecessarily difficult

Assignment

Create data-driven insight into machine performance and bottlenecks, and translate that into improvements that make planning more reliable and can be monitored structurally over time.

Approach / What I Did

1. Value Stream Mapping

Set up a Value Stream Map (VSM) to make flow, wait times, and process bottlenecks visible. This provided an initial overview of where time was lost.

2. Collect and Clean Data

Collected and cleaned machine and process data (SAP/Excel) and translated it into consistent definitions/KPIs. Without this step, reliable analysis was impossible.

3. Power BI Dashboard

Developed a Power BI dashboard that automatically shows daily:

How efficiently machines have worked
Where bottlenecks were and how long they lasted
Trend development so improvements are continuously monitored

4. Capacity vs. staffing analysis

Analyzed capacity vs. staffing: comparison between available workplaces/machines and staff planning. This clearly showed where the mismatch was.

5. Improve SAP Processing Times

Developed a new working method for SAP processing times so planning is based on realistic times instead of historical/incorrect values.

Methodology

The approach combined Lean Manufacturing principles (VSM, bottleneck analysis) with modern analytics tools (Power BI) and ERP optimization (SAP). This ensured improvements weren't just visible, but also structurally embedded and continuously monitored.

Result / Delivery

Automated Power BI dashboard with daily monitoring of machine efficiency and bottlenecks (continuous insight + improvement tracking)
Workforce planning insight: demonstrated staffing often didn't match available workstations/machines—only ~16% of the time the staffing level was a good fit
Improved SAP operation times: where times were previously accurate only ~3% of the time, the new approach provides a much more reliable basis for planning
Practical impact: easier and better planning + clearer, more reliable customer communication about what will be ready when

16%

RIGHT-SIZED STAFFING

Previously: unknown what percentage was correct

3% → ✓

SAP TIMES

From ~3% accurate to a reliable planning basis

100%

AUTOMATED

Dashboard updates daily without manual work

Practical impact for the organization

Planning: realistic time estimates improve schedule reliability
Customer communication: clearer expectations on lead times and delivery dates
Continuous improvement: dashboard makes bottlenecks immediately visible
Capacity management: insight into over/understaffing supports better rostering
Data-driven decisions: from "gut feel" to "knowing"

Skills

Process analysis • Data analysis • Power BI dashboards • SAP/Excel • Bottleneck & capacity analysis • Implementation-driven improvement • Value Stream Mapping • Manufacturing operations

Interested in Collaboration?

I help organizations with event management and process optimization

Get in touch

Schunk Xycarb Technology – Operations Performance & Planning