Service TAT giving you grief?
Here is a summary of a client success story that leveraged
the power of Artificial Intelligence (AI) to help them get answers
from their data and enable them to take control.
- UTL Solar, a Delhi-based B2C Electronics company
- Their Service department receives Repair / Service
requests across the country
- High TAT (Turn-Around-Time) affecting resource
utilization (people, inventory, cash-flow), logistics, training
They were facing too many problems in service and were not
able to find what has to be done to improve our service.
- Which service engineer is doing how much complaints?
- At what time?
- Is he starting his work at 11 or before 11?
- What area is the most problematic area?
- Which component is the most required component?
- Which issue is the biggest issue?
- Look at the Right-side JF Insights snippet, they can
quickly focus on areas of improvement
- They could filter by state, city, product and time
- JF Insights helped them identify the engineers that have
a high number of open requests AND high TAT across products,
engineers and areas/city
- Reduced bias in assessing high performing engineers
- Within 6 months: Service TAT reduced from 7.8 to 1.6 (75%
- Improved service level for clients
- Better control on resources across people, inventory, and
AI is a powerful enabler!
Insights that used to take days and weeks, can be done in
minutes and hours now.