Analytics that drives decisions, not reports.
Five practice areas under one roof. Each has its own maturity diagnostic, reference artifact, and engagement model. Click a tab to see how we work in your area.
8+
Planning analytics builds shipped across CPG, industrial, healthcare, and 3PL
12wk
Typical IBP scorecard build, brief to production with adoption plan
87%
Median planning team adoption at 90 days, measured by login data
3d → same day
Typical S&OP close compression after the IBP scorecard ships
Featured Practice
IBP & Planning Practice
The analytics layer that turns IBP, supply planning, and procurement into decisions your operating team will act on. This is where BaszGroup goes deepest.
IBP & Planning Maturity Diagnostic
Six questions. Sixty seconds. No email required. Your answers do not leave this page.
1 of 6
Q1 / IBP Cadence
How long does your monthly S&OP or IBP cycle take to close?
Q2 / Demand Consensus
How is demand consensus across sales, marketing, and finance tracked today?
Q3 / Financial Reconciliation
When do you reconcile the supply plan to the operating financial plan?
Q4 / Tooling
What does your planning team mostly rely on day to day?
Q5 / Ownership
If a forecast variance crosses a threshold tonight, who acts on it tomorrow morning?
Q6 / Scale
What is your revenue band? This calibrates the cost estimate.
Your Readout
Planning Analytics Maturity
STAGE 01
Spreadsheet & Meetings
Excel exports, no shared scorecard, IBP runs on slides
STAGE 02
Static Dashboards
BI built once, used in meetings, no reconciliation logic
STAGE 03
Cadence Aligned
Dashboards tied to IBP rhythm, named owners, exceptions
STAGE 04
Scenario & Predictive
What if modeling, financial reconciliation, predictive flags
What is likely happening inside your IBP cycle
Likely Cost
Integrated Business Planning Scorecard
Live demo with synthetic data. Cadence aware view of demand consensus, supply feasibility, and financial alignment across the monthly IBP cycle.
Demand Consensus
82.4%
+ 6.1 pts vs prior
Supply Feasibility
91.7%
+ 2.3 pts
Financial Plan Alignment
94.1%
+ 1.8 pts
Open Exceptions
14
+ 3 vs prior
S&OP Cycle Progress
Five step monthly cadence, current state
STEP 01
Demand Review
Closed Sep 3
STEP 02
Supply Review
Closed Sep 10
STEP 03
Reconciliation
In progress
STEP 04
Pre IBP
Sep 22
STEP 05
Executive IBP
Sep 28
Demand Consensus by Segment
Sales vs marketing vs finance signal
CPG North94%
CPG South88%
Industrial78%
Foodservice64%
Retail Pvt Label82%
Plan vs Actual, Rolling 6 Months
Volume index, planned and realized
| Open Exception | Segment | Owner | Impact | Status |
|---|---|---|---|---|
| Capacity shortfall, Plant 4, Nov | CPG North | VP Manufacturing | $1.8M revenue at risk | Risk |
| Forecast skew, foodservice Q4 | Foodservice | Demand Lead | 14% variance vs sales | Watch |
| Commodity exposure, cocoa | CPG South | Procurement Lead | 3.2 pts margin risk | Watch |
55sites
Largest multi-site WMS control tower BaszGroup has shipped to date
15min
Median exception detection time after instrumentation, down from shift end
8wk
Typical control tower build, brief to live across the network
5+
WMS platforms supported in production: Manhattan, Blue Yonder, Körber, and others
Practice 02
Control Tower & WMS Visibility
Multi-site warehouse operations visibility for VP Distribution and DC Operations leaders. Throughput against plan, labor utilization, and real time exception management across the network.
Control Tower & WMS Visibility Diagnostic
Six questions. Sixty seconds. Built for VP Distribution and DC Operations.
1 of 6
Q1 / Visibility
How do you currently see throughput across your warehouse network?
Q2 / Exception Detection
How quickly do you find out when a site is missing its throughput plan?
Q3 / Labor Utilization
How is labor utilization tracked across sites?
Q4 / Cross Site Comparability
Can you compare site performance on the same metrics, fairly?
Q5 / Action Loops
When the control tower flags a problem, what happens next?
Q6 / Network Scale
How many sites are in your warehouse network?
Your Readout
Control Tower Maturity
STAGE 01
Reports & Calls
Daily reports, no shared view, exception detection at shift end
STAGE 02
Per Site Dashboards
Each site has its own dashboard, no cross-site comparability
STAGE 03
Network Visibility
Single network view, standardized metrics, hourly updates
STAGE 04
Real Time Control
Real time exceptions, named playbooks, automated action loops
What is likely happening across your warehouse network
Likely Cost
Multi-Site WMS Control Tower
Live demo with synthetic data. Real time throughput, labor utilization, and exception flow across a five site warehouse network.
Throughput vs Plan
96.2%
on shift
Labor Utilization
88.4%
+ 2.1 pts
Open Exceptions
7
3 critical
Order Cycle Time
2.4 h
- 0.3 h
Throughput by Site, Current Shift
Units per hour vs plan
Exceptions by Type, Last 24h
Open and resolved exception flow
Picking12
Receiving4
Replen18
Putaway3
Yard8
| Site | Region | Throughput | Labor Util | Open Exc. | Status |
|---|---|---|---|---|---|
| DC East, Allentown | Northeast | 104% | 91.2% | 1 | On Plan |
| DC South, Atlanta | Southeast | 88% | 79.4% | 3 | Lagging |
| DC Mid, Chicago | Midwest | 102% | 90.1% | 1 | On Plan |
| DC West, Reno | West | 98% | 86.3% | 2 | On Plan |
7days
Typical monthly operating review prep time, down from 2+ weeks
6wk
Typical exec scorecard build, brief to first board ready cycle
100%
Of metrics ship with named owners and operating plan linkage
12+
Board ready scorecards built across CSCO and COO sponsors
Practice 03
Executive & Operational Reporting
Board ready supply chain reporting, monthly operating reviews, and exec scorecards. Built for the CSCO, COO, and CFO who need a defensible single source of truth.
Executive Reporting Maturity Diagnostic
Six questions. Sixty seconds. Built for executive sponsors of supply chain reporting.
1 of 6
Q1 / Source of Truth
How does your exec team currently get supply chain numbers?
Q2 / Prep Effort
How long does monthly operating review prep take your team?
Q3 / Definition Consistency
If you ask 3 leaders for OTIF, do you get the same number?
Q4 / Operating Plan Linkage
Are the metrics in your exec reports tied back to the operating plan?
Q5 / Narrative
When numbers move, do execs know why before the meeting?
Q6 / Scale
What is your revenue band? This calibrates the cost estimate.
Your Readout
Executive Reporting Maturity
STAGE 01
Inconsistent Decks
Different numbers each month, multi week prep, no clear source
STAGE 02
Assembled Reporting
One deck, but built manually, weak operating plan linkage
STAGE 03
Reconciled Scorecard
Single source, mostly automated, financial reconciliation
STAGE 04
Board Ready by Design
Named commentary, operating plan linkage, same day prep
What is likely happening inside your exec reporting cycle
Likely Cost
Monthly Operating Review Scorecard
Live demo with synthetic data. Board ready supply chain view: cost to serve, perfect order, inventory health, and named commentary per metric.
Cost to Serve
$4.82
- $0.18 vs plan
Perfect Order
94.6%
+ 1.2 pts
Inventory Health Index
82
flat MoM
OTIF
91.4%
- 0.6 pts
Cost to Serve by Business Unit
Current month vs operating plan
Operating Plan Variance, Trailing 6mo
Cost vs plan, indexed
| Metric | This Month | vs Plan | Owner | Named Commentary |
|---|---|---|---|---|
| Cost to Serve | $4.82 | - $0.18 | VP Logistics | Carrier rebid + mode shift to LTL holding |
| Perfect Order | 94.6% | + 1.2 pts | VP Distribution | DC Mid stabilized after WMS hypercare |
| Inventory Health | 82 | flat | VP Planning | Slow movers up 4 pts, offset by faster turn on A items |
| OTIF | 91.4% | - 0.6 pts | VP Distribution | DC South labor shortfall on Tuesday shifts |
3tiers
Strategic, operational, and tactical KPI cascade designed for every engagement
100%
Of metrics shipped with a named owner and documented threshold
4wk
Typical KPI architecture engagement, brief to documented framework
40+
Standardized supply chain metrics in the BaszGroup reference library
Practice 04
KPI Architecture & Scorecards
The metric hierarchy work that makes a dashboard get used after launch. Strategic to tactical cascades, named ownership, threshold logic, and escalation paths.
KPI Architecture Maturity Diagnostic
Six questions. Sixty seconds. Built for analytics leaders and operating sponsors.
1 of 6
Q1 / Hierarchy
Do your KPIs cascade from strategic down to tactical?
Q2 / Named Ownership
Does every metric have a named owner who acts when it moves?
Q3 / Thresholds
Do your KPIs have documented green / yellow / red thresholds?
Q4 / Escalation
When a KPI crosses a threshold, is the escalation path documented?
Q5 / Review Cadence
How often is the KPI framework itself reviewed and revised?
Q6 / Scale
What is your revenue band? This calibrates the cost estimate.
Your Readout
KPI Architecture Maturity
STAGE 01
Flat Metrics List
No cascade, implicit ownership, no thresholds
STAGE 02
Partial Framework
Some hierarchy, partial ownership, arbitrary thresholds
STAGE 03
Documented Cascade
Cascade exists, named owners, thresholds set
STAGE 04
Living Framework
Reviewed quarterly, escalation documented, plan linked
What is likely happening in your KPI framework
Likely Cost
Supply Chain KPI Hierarchy
A three tier cascade designed to be defensible at every level. Each tier has named owners and the linkage that lets a strategic miss decompose to a tactical cause.
Strategic
Total Supply Chain Cost % of Revenue
OWNER:CSCO
Perfect Order Rate
OWNER:COO
Cash to Cash Cycle Time
OWNER:CFO
Operational
OTIF (On Time In Full)
OWNER:VP Distribution
Inventory Turns by Business Unit
OWNER:VP Planning
Cost to Serve per Order
OWNER:VP Logistics
Tactical
Pick Accuracy by DC
OWNER:DC Manager
Forecast Accuracy by SKU class
OWNER:Demand Planner
Carrier On Time Pickup
OWNER:Transportation Lead
| Metric | Tier | Green Threshold | Red Threshold | Review Cadence |
|---|---|---|---|---|
| Perfect Order Rate | Strategic | ≥ 95% | < 90% | Monthly |
| OTIF | Operational | ≥ 93% | < 88% | Weekly |
| Pick Accuracy | Tactical | ≥ 99.5% | < 98.5% | Daily |
| Forecast Accuracy | Tactical | ≥ 80% | < 70% | Monthly |
22K+
Suppliers, vendors, and trade partners integrated across client engagements
12+
Source systems typically consolidated per engagement: ERP, WMS, TMS, OMS, EDI
10wk
Typical data foundation build, brief to first production pipelines
99.4%
Pipeline uptime target across active engagements, monitored continuously
Practice 05
Data & ETL Foundation
The pipelines, integrations, and master data work that make the analytics layer honest. Multi system consolidation, EDI and API integration, and the foundation under everything BaszGroup ships.
Data Foundation Maturity Diagnostic
Six questions. Sixty seconds. Built for data leaders and analytics sponsors.
1 of 6
Q1 / Source Systems
How is data from your ERP, WMS, TMS, and other systems brought together?
Q2 / Master Data
Is your master data (SKU, customer, vendor, location) reconciled across systems?
Q3 / EDI & Partner Integration
How are you connected to suppliers, customers, and 3PL partners?
Q4 / Data Quality
When the analytics layer disagrees with reality, how do you find out?
Q5 / Documentation
If your data engineer left tomorrow, would the pipelines be operable?
Q6 / Scale
What is your revenue band? This calibrates the cost estimate.
Your Readout
Data Foundation Maturity
STAGE 01
Manual & Brittle
Email pulls, Excel, tribal knowledge, frequent breakage
STAGE 02
Partially Automated
Some scheduled pipelines, weak master data governance
STAGE 03
Orchestrated Pipelines
Mostly automated, monitored, documented gaps
STAGE 04
Governed Foundation
Master data governed, real time validation, runbooks
What is likely happening in your data foundation
Likely Cost
Supply Chain Data Foundation Architecture
The pipeline architecture under a typical BaszGroup engagement. Source systems flow through a transformation layer into the analytics layer, with validation and governance at each step.
Source Systems
ERP SAP / NetSuite / Oracle
WMS Manhattan / Blue Yonder / Körber
TMS MercuryGate / OTM / Project44
OMS + EDI 22K+ trade partners
Transformation Layer
Ingestion EDI / API / FTP / Batch
Master Data SKU / customer / vendor / location
Quality Checks Validation + named exception owners
Modeling Star schema + semantic layer
Analytics Layer
IBP Scorecard Monthly planning rhythm
Control Tower Real time WMS visibility
Exec Reporting Monthly operating review
KPI Scorecards Three tier cascade
22K+
Trade Partners
12+
Source Systems
99.4%
Pipeline Uptime
15 min
Data Latency Target
Anonymized Engagement
~$400M food distributor. 3 day S&OP close became same day. 14 manual reports retired. 87% planning team adoption at 90 days. 12 weeks end to end.
12 wkEngagement
87%Adoption
Start Here
Bring us your current analytics. We will tell you what to fix first.
The 30 minute working session is built around whichever practice area you choose. You leave with a one page readout of the highest leverage rebuild. No pitch, no obligation.
Book the working session →