Feras Hayf Portfolio case study
Business analysis · Excel · Power BI

Order Operations & Performance Analysis

Why premium orders arrived late or damaged, and how one shared tracker and dashboard can fix it.

Independent case study Inspired by professional experience. Company and data are fictional.
ProblemAnalysisExcelPower BIInsights
02

Customers paid for premium and got delays

1 in 4
orders missed the promised delivery date
7.4%
arrived damaged or with items missing
Root cause Each team tracked orders in its own place. No one saw the full picture.
Email Paper logs Courier portal
ProblemAnalysisExcelPower BIInsights
03

Information got lost at every hand-off

I mapped the order journey with the five team leads. Each gap became a requirement.

Team
Customer service
Procurement
Warehouse
Quality check
Shipping
Gap
Details re-typed into emails
Supplier replies not logged
Arrivals not time-stamped
Checks often skipped
Tracking not linked to order
Requirement
One shared order ID
Time target per stage
Date stamp at each step
QC required before dispatch
Status visible to all
Solution A shared Excel tracker as the single record, feeding a Power BI dashboard for weekly review.
ProblemAnalysisExcelPower BIInsights
04

One shared record for every order

Order_Tracker_2026.xlsx Excel · Snapshot 16 Jun 2026
FileHomeInsertFormulasDataView
H3 fx =IF(D3="Delivered","Delivered",IF(TODAY()>G3,"Late",IF(E3>F3,"At risk","On track")))
ABCDEFGHIJ
1Order IDOrderedOriginStageDaysSLAPromisedStatusQCDelay reason
2PO-1184205-Jun-26USShipping1212-Jun-26LatePassProcurement +3 days
3PO-1187309-Jun-26USProcurement5216-Jun-26At risk—Supplier not confirmed
4PO-1188110-Jun-26EUWarehouse21.517-Jun-26At risk—Receiving backlog
5PO-1189011-Jun-26GCCQuality check1118-Jun-26On track—
6PO-1190212-Jun-26USProcurement2219-Jun-26On track—
7PO-1190706-Jun-26GCCDelivered——13-Jun-26DeliveredPass1 item missing
8PO-1191114-Jun-26EUCustomer service20.521-Jun-26At risk—Address incomplete
Orders Stage_Log SLA_Lookup Dept_Summary 1,200 rows
XLOOKUPPulls each stage's SLA and latest time stamp
IF + TODAYSets status to On track, At risk or Late
Conditional formatHighlights late and at-risk orders
COUNTIFSFeeds the department summary and Power BI
ProblemAnalysisExcelPower BIInsights
05

Performance by team, at a glance

Order Performance Power BI
MonthJan – Jun▾
TeamAll▾
OriginUSEUGCC
Orders1,200
On time75%
Avg delivery9.6 days
Damaged7.4%
Late orders by team
Procurement
114
Warehouse
72
Shipping
54
Quality check
39
Customer service
21
Days in stage vs targettarget
Procurement
3.6
Warehouse
2.1
Shipping
1.9
Quality check
1.2
Customer service
0.8
ProblemAnalysisExcelPower BIInsights
06

What the data shows, and what to do

38%
of late orders got stuck in procurement
Action48-hour supplier reply rule, with an auto-alert
63%
of damaged orders skipped the quality check
ActionNo dispatch without a recorded QC pass
2×
US orders were late twice as often as GCC orders
ActionSet delivery promises by origin
Conclusion 07

One view of every order, from purchase to doorstep

Clear process Excel tracker Power BI dashboard
On-time delivery
75%→90%
Damaged orders
7.4%→<3%
Weekly reporting
6 h→30 min
Pilot targets, not measured results.
Feras Hayf