CMWSSB Complaint Analytics

Street	Depot	Complaints	People
Iyyam Perumal Street	DEP 119	5	4
Begum 3Rd Street	DEP 119	2	2
Begum Main Road	DEP 119	2	1
C.i.t. Colony 1St Main Road	DEP 119	2	2
Jawahar Hussain Khan 3Rd Street	DEP 119	2	2
Peters Road	DEP 119	2	1
Pooramprakashrao Road	DEP 119	2	2
Venkatachalam Street	DEP 119	2	2
C.i.t. Colony 2Nd Main Road	DEP 119	1	1
Chanda Shahib Street	DEP 119	1	1
Lakshmipuram 2Nd Street	DEP 119	1	1
Mayor Sivaraj Street	DEP 119	1	1

🛠 Sewer Complaints (main block · house block · overflow)

CSV PDF

Street	Depot	Sewer	People
Venkatachalam Street	119	79	43
Pooramprakashrao Road	119	74	22
Periya Malaiyappan Street	119	61	26
Peters Road	119	40	15
Thippu Street	119	37	16
T.v.k Road (Royapet Highroad)	119	36	26
Judge Jumbulingam Road	119	33	14
Mustura Begum Pettah Street	119	33	17
Begum Main Road	119	27	16
Saiva Muthiah Mudali 6Th Street	119	25	8

🚰 Water Complaints (no supply · short supply · leaks)

CSV PDF

Street	Depot	Water	People
Venkatachalam Street	119	21	16
Gangai Amman Koil Street	119	20	7
Kandasamy Lane	119	18	2
Pooramprakashrao Road	119	12	4
Begum Main Road	119	11	8
Iyyam Perumal Street	119	10	3
Sri Krishnapuram Street	119	9	9
C.i.t. Colony 1St Cross Street	119	8	4
T.v.k Road (Royapet Highroad)	119	7	6
14/3 New No - 35- Gangai Amman Koil Street	119	6	1

💧 Water Pollution (pollution complaints)

CSV PDF

Street	Depot	Pollut.	People
Mavadi Vinayagar Koil Street	119	8	4
Peters Road	119	6	5
Begum 3Rd Street	119	5	5
Kandasamy Lane	119	5	2
Gangai Amman Koil Street	119	4	3
Mohammed Hussain Khan Street	119	4	3
Nallanna Mudali Street	119	4	3
Sripuram Lane	119	4	2
Venkatachalam Street	119	4	4
Avvai Shanmugam Salai	119	3	3

🔁 Recurrence — how often the same issue comes back (same category · same street)

PDF

Category	Street	Depot	Times	Span (days)	Avg gap (days)	Per month
Others	Iyyam Perumal Street	119	5	103	25.9	1.45

Avg gap = average days between consecutive complaints of that type on that street. Lower gap / higher “per month” = a faster-recurring, unresolved problem.

🔬 Advanced Analysis

Pareto — the vital few (which categories drive most complaints)

Categories ordered by volume with their cumulative share. The highlighted rows are the smallest set that together account for ~80% of all complaints — fix these first.

Category	Count	Share	Cumulative
Others vital	24	100%	100%

When complaints arrive (weekday × time of day)

Load pattern across the week — darker cells are busier six-hour windows. Useful for staffing and planning proactive checks before the peak.

	Night	Morning	Afternoon	Evening	Total
Mon		1	4		5
Tue		1	4	1	6
Wed	2	1	1		4
Thu	1	1	1		3
Fri		2	1		3
Sat		1	1		2
Sun			1		1
Total	3	7	13	1	24

Linked problems (category pairs that hit the same streets)

Pairs of issue types that recur together on the same street, ranked by the number of streets where both appear. Strong pairs point to a shared root cause worth fixing in one visit.

Problem A	Problem B	Shared streets
Not enough overlapping complaints in this scope.