CMWSSB Complaint Analytics

Street	Depot	Complaints	People
Dr. Besant Road	DEP 115	5	4
R.o.b Vi Street	DEP 115	3	3
Mirza Hyder Alikhan Street	DEP 115	2	2
Perumal (M) Street	DEP 115	2	2
Dr. Nayamadullah Shahib Street	DEP 115	1	1
Feroz Sahib Street	DEP 115	1	1
Gafoor Shahib 2Nd Lane	DEP 115	1	1
Hakkim Maqdoom Ashraf Street	DEP 115	1	1
Hussian Nagar Iv Street	DEP 115	1	1
Hussian Nagar V Street	DEP 115	1	1
Indira Garden Street	DEP 115	1	1
Jani Johankhan II Lane	DEP 115	1	1

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

CSV PDF

Street	Depot	Sewer	People
Muzafar Jung Bahadur Street	115	59	25
Surappa Mudali Street	115	46	15
R.o.b I Street	115	37	13
Jani Johankhan Road	115	32	22
Koya Arunagiri 5Th Street	115	29	10
Perumal (M) Street	115	27	19
Mallan Ponnappa Mudali Street	115	25	14
Hakkim Maqdoom Ashraf Street	115	23	9
Mir Bakshi Ali Street	115	23	14
Peters Road	115	23	11

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

CSV PDF

Street	Depot	Water	People
Mallan Ponnappa Mudali Street	115	4	3
Perumal (M) Street	115	4	4
Thirunavukarasu Street	115	4	3
Surappa Mudali Street	115	3	3
Dr. Nayamadullah Shahib Street	115	2	1
Koya Arunagiri 1St Street	115	2	2
Muzafar Jung Bahadur Street	115	2	2
Nair Iyya Street	115	2	2
R.o.b I Street	115	2	2
Whites Lane	115	2	2

💧 Water Pollution (pollution complaints)

CSV PDF

Street	Depot	Pollut.	People
Thalayari Street	115	18	6
Koya Arunagiri 1St Street	115	11	9
Nair Varatha Street	115	6	6
Hussain Alikhan II Street	115	5	4
Nair Iyya Street	115	5	1
Perumal (M) Street	115	5	3
Dr. Besant Road	115	3	3
Gafoor Shahib 1St Lane	115	3	2
Gafoor Shahib Street	115	3	1
Koya Arunagiri 2Th Street	115	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	Dr. Besant Road	115	5	414	103.4	0.36

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	33	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		4			4
Tue		1	5		6
Wed		1	3	1	5
Thu		2	3	1	6
Fri		3	3		6
Sat			3	1	4
Sun			2		2
Total	0	11	19	3	33

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.