MERIDIAN · Command Center · Surya Bakers Pvt. Ltd.
AS

Good morning, Anika. Plans for December are ready.

A unified pulse across forecast, supply, and logistics — refreshed continuously from your ERP, sales, and dispatch feeds. No more eight Excel tabs.

Forecast Accuracy
91.4%
▲ 4.2 pts vs Nov
OTIF Service Level
96.8%
▲ 1.6 pts
Capacity Utilisation
82.3%
▲ 6.8 pts
Logistics Cost / Kg
₹4.18
▼ ₹0.42 vs Nov
Inventory Days
11.6d
▼ 2.1 days
Fill Rate
98.1%
▲ 0.9 pts

Demand vs. supply, twelve-month horizon

All SKUs · units in '000 cases

Category mix

Approved Dec forecast
Biscuits34.2%
Bread22.8%
Snacks15.4%
Cookies12.1%
Cakes9.6%
Rusk5.9%

Zone scoreboard

Forecast attainment, last 30 days

Today's signals

System recommendations · auto-prioritised
3 require attention
Jaipur Unit · Line 3 bottleneck on Marie Biscuits 200g

Projected demand outpaces line capacity by 14% in week 51. Recommend shifting 8,400 cases to Mumbai Unit Line 1 — slack available.

→ Recovers ₹6.2 L margin · 0 SLA risk
South zone freight: open 32 ft slot to Chennai

Three 20 ft trips to Chennai run at 72% load. Consolidating to one 32 ft saves trips on Mon & Wed.

→ ₹1.14 L / month · −0.6 ₹/kg
Choco Chip Cookies 200g · holiday uplift detected

Historic Dec lift +18%. Current S&OP uplift set at 9%. Suggest revising to 17% before locking week 50.

→ Avoids stock-out across N + W zones

Bring your data in. We'll do the rest.

Drop Excel or CSV files for sales history, SKU master, capacity, and logistics. Meridian validates schema, reconciles SKUs across feeds, and triggers the forecast engine automatically.

Upload data sources

.xlsx · .xls · .csv · up to 200 MB each

Drag files here, or click to browse

Recognised: sales_history, sku_master, zone_sales, capacity, logistics, warehouse

XLS
sales_history_FY24-25.xlsx
128,440 rows · 14 SKUs · 24 months · Validated ✓
Ingested
XLS
sku_master_Dec.xlsx
14 SKUs · 6 categories · MRP + MOQ linked
Ingested
CSV
zone_sales_north_south.csv
82,116 rows · 5 zones · daily granularity
Ingested
XLS
capacity_plants_Q4.xlsx
4 plants · 11 lines · shift patterns
Ingested
CSV
logistics_dispatch_Nov.csv
5,840 trips · 20ft & 32ft fleet
Mapping
XLS
warehouse_master.xlsx
8 warehouses · capacity & service area
Ingested

Ingest pipeline

Live · last event 12 sec ago
Schema detected · 6 of 6 files recognised
SKU reconciliation · 14 SKUs · 0 orphans
Unit harmonisation · kg ↔ cases ↔ trays
4
Outlier scrub · removing 0.4% anomalous rows
5
Seasonality decomposition
6
Forecast engine warm-up

Detected categories

🍰 Cakes · 2 🍪 Biscuits · 3 🍞 Bread · 3 🥨 Snacks · 2 🥖 Rusk · 2 🍫 Cookies · 2

SKU master · preview

Auto-parsed from upload · 14 of 14 rows shown
SKUNameCategoryPackMRP ₹MOQ (cases)PlantLast yr · qty

Forecast, four ways. Pick the winner per SKU.

Meridian fits every SKU against four classical methods and surfaces the one with the lowest error. Override any pick with a click.

Forecast Accuracy
91.4%
▲ 4.2 vs prior method
MAPE
8.6%
▼ 3.1 pts
Bias
+1.2%
slight over-forecast
Tracking signal
0.32
Within control band

Method comparison · Marie Biscuits 200g

Actual vs. fitted, 24 months · cases
Actual Selected forecast Alternatives

Last month: forecast vs actual

Top SKUs by volume

Seasonality heatmap · monthly index by SKU

100 = annual average · derived from 24-month history

Zone-wise forecast · December

All SKUs aggregated · cases

Quarterly outlook

Forecast + 95% confidence band

S&OP alignment · December cycle

One number plan. Sales, supply chain, and management converge on a single approved forecast — with overrides tracked and audited.

Workflow

3 of 3 approvals · in flight
① Sales team
Priyanka R · Head of Sales
Approved · Dec 6
② Supply chain
Karan M · Planning lead
Approved · Dec 7
③ Management
Anika S · COO
Pending · awaiting sign-off

Consensus forecast · all SKUs

Editable. Tab to navigate. Overrides write to audit log.
Promo uplift active · +8.5% Seasonal index applied
SKU Name Statistical Fc Seasonal % Last yr Dec Suggested final User override Approved Fc Status

Production, balanced across four plants.

Approved forecast becomes a feasible production plan in seconds — line by line, shift by shift, day by day. Bottlenecks flag themselves.

Plant utilisation · December plan

Planned production ÷ available capacity
Jaipur Unit
88%
88%
Mumbai Unit
74%
74%
Kolkata Unit
69%
69%
Bangalore Unit
94%
94%

Line-level view · Bangalore

L1 · Biscuits
97%
Bottleneck
L2 · Cookies
91%
High
L3 · Rusk
82%
OK

Production vs capacity

December · cases
Planned
2.41 L
Capacity
2.93 L
Slack
17.7%

Daily production calendar · December

All plants aggregated · darker = higher load
Light
Moderate
High
Peak

SKU-wise production plan

Top 14 SKUs · December · cases
SKUNamePlantLine Approved FcPlan qty Run hrsUtil %Shift mix

Logistics, orchestrated end to end.

Fleet, route, freight, SLA — one plan that loads the right truck on the right lane at the right cost per kilogram.

Trucks required (daily avg)
48
26× 20ft · 22× 32ft
Load utilisation
89.4%
▲ 7.1 pts
Cost / kg
₹4.18
▼ ₹0.42
Freight saved · MTD
₹14.6L
▲ 22% vs Nov

Destination-wise dispatch plan

Week 50 · top 8 lanes
Route-optimised
Origin → DestinationVolume (t)TripsVehicle mixLoad %Cost ₹/kg
Jaipur → Delhi NCR128.4128× 32ft 4× 20ft93%3.42
Mumbai → Pune84.699× 20ft88%2.86
Mumbai → Ahmedabad61.265× 32ft 1× 20ft91%3.84
Bangalore → Chennai72.876× 32ft 1× 20ft94%3.61
Bangalore → Hyderabad58.466× 32ft89%3.92
Kolkata → Bhubaneswar42.655× 20ft86%4.18
Kolkata → Guwahati38.444× 32ft82%5.84
Jaipur → Lucknow46.253× 32ft 2× 20ft90%3.96

Fleet mix recommendation

Week-on-week, by tonnage

Vehicle economics

VehicleCapacityCost/trip₹/kg @ 90%
20 ft container9 t₹24,8003.06
32 ft single-axle14 t₹34,2002.71
32 ft multi-axle21 t₹46,5002.46

Daily truck requirement

Next 14 days · 20ft + 32ft mix

Cost vs SLA frontier

Each lane plotted · sweet spot in green band

A hub-and-spoke built for India.

Optimise where to stock, where to serve from, and where to invest next. Volume, SLA, and freight cost solved as one objective.

Network topology

4 plants · 8 warehouses · 26 service zones
Plant Warehouse Proposed hub
JAIPUR PLANT · 38 kt/mo MUMBAI PLANT · 42 kt/mo KOLKATA PLANT · 24 kt/mo BANGALORE PLANT · 28 kt/mo DELHI WH NAGPUR WH BHUB. WH CHENNAI WH HYD WH AHM. WH LKO WH GUW. WH PROPOSED · INDORE MERIDIAN · NETWORK OPTIMISATION · DEC 2026
Plant
Warehouse
Proposed hub

If we add an Indore hub…

Modelled impact, full network re-solve
17.4%
Logistics cost reduction
Transit time, central zones −1.8 days
SLA compliance 94 → 98.4%
Annual freight savings ₹3.6 Cr
CAPEX payback 19 months
Inventory days · central 14 → 9

Warehouse servicing matrix

Recommended primary & secondary sources per zone
North Zone

Primary: Jaipur Plant · Delhi WH
Secondary: Lucknow WH

Transit 6h · OTIF 99.1%
West Zone

Primary: Mumbai Plant · Ahmedabad WH
Secondary: Nagpur WH

Transit 8h · OTIF 97.6%
South Zone

Primary: Bangalore Plant · Chennai WH
Secondary: Hyderabad WH

Transit 9h · OTIF 96.2%
East Zone

Primary: Kolkata Plant · Bhub. WH
Secondary: Guwahati WH

Transit 11h · OTIF 94.8%
Central Zone New

Primary: Proposed Indore Hub
Secondary: Nagpur WH

Transit 5h · projected OTIF 98.4%
Network health

97.2% of demand served within SLA. 6 lanes flagged for review next cycle.

Re-solve scheduled · Jan 4

Executive analytics.

Drill into any KPI, any zone, any SKU. The board view your CFO actually opens.

Service level

By zone · last 30 days

Inventory days

By category · target = 12d

Margin contribution

Top SKUs · MTD

Plan vs actual · cascade

Forecast → Production → Dispatch → Sales

Where we won, where we lost

Variance vs plan · top movers
Choco Chip Cookies · West +21.4%
Marie Biscuits 200g · North +14.8%
Suji Rusk 300g · East +11.2%
Aloo Bhujia · South −6.8%
Brown Bread · Central −4.2%
White Sandwich · East −3.1%

Value at stake · scenario stress tests

If Meridian's recommendations are implemented in full
Manual planning hours saved
320h
per month, across 6-person planning team
Forecast accuracy uplift
+9.2pts
from 82.2% (Excel baseline) → 91.4%
Annualised financial impact
₹8.2Cr
freight + working capital + obsolescence combined