Price Optimization + Tableau: Built for VP Supply Chain
Most retailers discover Pricing problems too late. Ward delivers automated insight cards — what changed, why, and what to do — while there's still time to act. Your Supply Chain team has the data. What they don't have is bandwidth to find what's buried in it.
Price Optimization powered by Tableau
Price Optimization is the process of ward monitors price elasticity shifts in real time and recommends adjustments that protect margin without sacrificing volume.
When connected to Tableau, Ward reads tableau hyper extracts, underlying database (direct), published data source metadata and enriches them with contextual signals to generate pricing insight cards. Ward connects to the same databases Tableau uses. Or reads Tableau Server metadata via REST API for context.
How Ward delivers Pricing insight cards: Ward continuously measures price elasticity by category, tracks competitive pricing signals, and models the margin-volume tradeoff.
Key capabilities
- Real-time elasticity measurement
- Category-level price sensitivity
- Competitive price monitoring
- Margin-volume tradeoff modeling
How Ward connects to Tableau
Ward does not replace Tableau. Ward adds the proactive layer Tableau lacks. When a metric moves, Ward explains why and recommends action.
Setup: Ward connects to the same databases Tableau uses. Or reads Tableau Server metadata via REST API for context.
Data Ward reads from Tableau
Impact metrics with Tableau
Data lake enrichment
Ward enriches Tableau data with: Tableau data sources, Underlying database, Weather & events, Competitor pricing, Customer data
You find out about stockouts after customers do.
- ×Demand forecasts are off by 15-25% and nobody catches it until the shelf is empty
- ×Supplier fill rate issues are discovered at receiving, not predicted
- ×Safety stock levels are set annually, not dynamically
- ×No early warning system for supply chain disruptions
- ×Replenishment exceptions require manual triage every morning
- ✓Stockout prediction cards arrive 24-72 hours before empty shelves
- ✓Supplier fill rate tracking with automatic escalation
- ✓Dynamic safety stock recommendations based on current demand signals
- ✓Weather, event, and macro-driven demand adjustments
- ✓Replenishment exceptions auto-prioritized by revenue impact
Stockouts cost retailers $1.14 trillion in missed sales globally each year. — IHL Group
What a Ward insight card looks like
Dairy category showing -1.4 elasticity this week vs -0.8 baseline. Consumers responding to price changes 75% more than normal.
Frequently asked questions
Ward connects to the same databases Tableau uses. Or reads Tableau Server metadata via REST API for context. Data points include: Tableau Hyper extracts, Underlying database (direct), Published data source metadata.
You find out about stockouts after customers do. Ward solves this with automated insight cards: Stockout prediction cards arrive 24-72 hours before empty shelves. Supplier fill rate tracking with automatic escalation. Dynamic safety stock recommendations based on current demand signals.
First insight cards arrive within 48 hours of data connection. Ward needs approximately 2 weeks to establish robust baselines for your specific operation.
No. Ward sits on top of your existing stack. It is the proactive intelligence layer that watches your data continuously and delivers insight cards — so your team acts on findings instead of hunting for them.
Related solutions
Insights surface
Ward’s agents detect what changed, why it matters, and what to do about it. Every insight includes a recommended action—not just a chart to interpret.
Insights become actions
Any insight card can be turned into a tracked ticket or task. Dispatched to the right person, on the right channel—mobile push, text, or email. Not every insight needs a ticket. But when one does, it has an owner.
Your team responds
Insights get voted up or down with reasoning. Tickets get completed or rejected. Every response is a signal—Ward learns what worked, what missed, and why.
Outcomes measured
Ward evaluates real results: revenue, margin, fill rate, labor cost. Did the action actually improve the number it targeted? Measured outcomes, not assumptions.
Agents get sharper
Every vote, every completed ticket, every measured outcome feeds back in. Ward learns from your team’s judgment and real-world results. Each cycle sharpens the next. Then it starts again.
See what pricing problems Ward catches.
Root causes, not just alerts. See it on your data.
Find out what your data has been hiding.
Tell us about your operation. We’ll show you the problems Ward catches — and the ones your current tools miss.