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Retail Decision Intelligence

Your Retail Data Has the Answers.
Your Ops Leaders Are Still Building Spreadsheets.

Patterson Consulting modernizes your retail data platform on Databricks and deploys the Decision Intelligence Agents that turn warehouse analytics into operational narrative — so your data team has infrastructure they're proud of and your ops leaders have answers they can act on.

The Challenge

Your Analytics Stack Moves Slower
Than Your Business

Retail runs on matching products to customers at the right place, time, and price. That requires decisions made quickly on accurate data — and most retail analytics stacks were not built for that speed.

Read: Decision Intelligence — closing the gap between data and business judgment

Week-Old Reports Driving Allocation

Store managers and regional directors are making replenishment and allocation decisions from reports that are days or weeks behind. By the time the data arrives, the stockout has already happened or the markdown is already necessary.

Inventory Variance Buried in Dashboards

Your dashboards surface the numbers. But getting from "shrink is up 4% at location 17" to "here is why, and here is what to do next" still requires an analyst to assemble the narrative — work that should be automated, not scheduled.

Ops Leaders Doing Analyst Work

Regional ops managers spend hours before every leadership meeting pulling, correlating, and assembling context from multiple systems. That time belongs to judgment and decisions — not to the execution work of finding and formatting data.

The Foundation + The Intelligence Layer

The data engineering work creates the platform. The Decision Intelligence layer creates the value your business leaders can see. Both decisions belong to the same conversation.

For VP Engineering / CTO

Databricks Data Foundation

A unified, governed data lakehouse that gives your data team the infrastructure to build on — and your operations teams a single version of the truth to work from.

  • Real-time ingestion from POS, e-com, loyalty, vendor EDI, and logistics via Lakeflow Connect
  • Governed semantic layer with Unity Catalog Metric Views — consistent KPIs across every team
  • Serverless SQL and Lakeflow Jobs — KPIs in minutes, not weekly batch
  • Lineage, access control, and audit trail across the full data stack
Migration to Databricks →
For COO / VP Ops / Regional Directors

Decision Intelligence Agent Layer

AI agents deployed on top of your data foundation that automate the execution-layer cognitive work — so your operations leaders get operational narrative answers, not more panels to interpret.

  • Automated weekly performance narratives for regional ops managers
  • Root-cause narrative for inventory variance — from data to recommended action
  • Demand and allocation signals surfaced in the format decision-makers actually use
  • Output integrates into your existing dashboards and reporting workflows
Decision Intelligence Service →

"The data engineering work creates the platform. The Decision Intelligence layer creates the value your business leaders can see."

For VP Engineering / CTO

Build the Data Foundation Retail Operations Require

Retail data is scattered — POS, e-com, loyalty, vendor EDI, logistics — making it hard to answer even basic questions: what's selling where, at what margin, and what do we order next? Patterson Consulting uses Databricks to unify these sources into a governed, near-real-time layer with reliable pipelines, standard schemas, and lineage.

The result is one operating picture with clear item/location margin and sell-through, timely allocation and replenishment signals, and faster decisions — built on the architecture your data team can actually own and maintain.

Learn About Migration to Databricks
Lakeflow Connect

Unified Retail Data Integration

Ingest and govern POS, e-com, loyalty, vendor EDI, and logistics into a single medallion architecture. Reliable pipelines, standard schemas, and full lineage — so every team works from the same version of the truth.

Serverless SQL + Lakeflow Jobs

Real-Time KPI Layer

Close the gap between events and decisions. Streaming and batch pipelines that deliver KPIs in minutes — not weekly batch runs. Fewer stockouts and markdowns because your team sees what's happening now, not last Tuesday.

Unity Catalog Metric Views

Governed Semantic Layer

Define metrics once. Use them everywhere. Unity Catalog Metric Views create a governed semantic layer so finance, operations, and merchandising all work from the same margin, sell-through, and fill-rate definitions.

Live Demo

See Decision Intelligence in Action

Watch how Decision Intelligence Agents analyze retail logistics data in real time — answering the operational questions your team is spending hours building manually today.

VP Eng sees the agent architecture running on Databricks. Ops leaders see the operational output — narrative answers grounded in governed data, delivered without a data team in the loop.

Learn About the Service
For COO / VP Ops / Regional Directors

Decision Intelligence Agents for Retail Line of Business

Recurring decisions that consume disproportionate execution time are the primary target for cognitive labor automation. Here are the highest-value candidates in retail operations.

Store Conversion Variance Review

District and regional managers lose review time debating whether one store's conversion decline is local execution or a district-wide pattern. This workflow assembles the store vs. prior period and district median comparison automatically — before the meeting.

Operations Live demo

Planogram Compliance Driver Attribution

When planogram compliance drops, merchandising teams need to prove whether the problem is inventory, store execution, or planogram fit. This workflow assembles the evidence, ranks the drivers, and produces a store-level remediation list — without requiring an analyst to pull the data.

Merchandising Live demo

On-Shelf Availability Variance

When a store's sales dip, district leaders need to know whether on-shelf availability is failing at that location or drifting across the district. This workflow delivers a period-over-period and district-median OSA comparison scorecard — ready before the escalation call.

Inventory Live demo

BOPIS Pickup Drift Detection

When a store's BOPIS pickup speed slips, district ops leaders need to know whether the issue is local or district-wide before the next escalation call. This workflow calculates store performance versus prior period and district median — in seconds, not a spreadsheet session.

Omnichannel Ops Live demo

Pick Productivity Driver Brief

When pick productivity drops, fulfillment coordinators need to know whether the problem is routing, exceptions, or order complexity before backlog builds. This workflow produces a ranked driver brief and action-ready shift handoff in minutes — not after the next planning cycle.

Fulfillment Live demo

Supply Chain Disruption Reroute Brief

When weather spikes and DC constraints collide, supply chain leads need to reconcile inventory positions, shipment ETAs, and demand signals fast enough to defend reroute decisions. This workflow produces a ranked driver brief and shipment action list in minutes — not after the crisis has already resolved.

Supply Chain Live demo

Retail Managers Shouldn't Be Doing Analyst Work

Every regional manager's day divides into two fundamentally different kinds of work: execution work (finding data, assembling context, formatting reports) and judgment work (making allocation, pricing, and staffing decisions). The first type is automatable by definition. The second is where the most experienced people in your organization create the most value.

A well-built Databricks foundation makes it possible to automate the execution layer. Decision Intelligence Agents make that automation operational. Together, they free your retail managers to do what they were hired to do.

Read: The Three Layers of Knowledge Work

Execution Layer

Data retrieval, report assembly, dashboard correlation, variance lookup. Repeatable, schedulable, automatable.

Target for automation Examples: weekly store summaries, inventory pull, sell-through reports

Judgment Layer

3–5×

Diagnosis, prioritization, allocation decisions, vendor negotiations. Amplified when freed from execution work.

Amplify with freed time Examples: allocation decisions, promotion planning, exception triage

Strategic Layer

7–10×

Category direction, assortment strategy, market positioning. Compounds over time. Gets more time when the other two layers are running efficiently.

Protect and invest in Examples: category strategy, vendor partnership decisions, assortment architecture
Free Tool

How Much Cognitive Labor Are Your Retail Teams Losing to Data Assembly?

Use our free Cognitive Labor Calculator to model the execution-layer time your regional managers, merch analysts, and ops leads spend on data assembly — and what it's worth when that time gets redirected to judgment work.

Try the Cognitive Labor Calculator
40–60%

of retail knowledge worker time is execution-layer labor — data assembly, report building, dashboard correlation

3–7×

value multiplier when execution time is redirected to allocation, merchandising, and operations judgment work

Hours

to build a working retail Decision Intelligence prototype — not months — using the Knowledge Work Foundry

Live Workshop

See Decision Intelligence Built for Your Retail Data, Live

Join our Decision Intelligence on Databricks workshop. Bring your data team and your ops leads. We'll identify your highest-value retail automation candidates, prototype a working agent against your actual workflows, and model the ROI — all in a single session.

Live functional area analysis of your retail org structure

Working retail Decision Intelligence prototype built during the session

Economic model you can take to your CFO and ops leadership

Register for the Workshop

From the Blog: Building Retail Intelligence on Databricks

Technical guides and architecture articles from the Patterson Consulting team

Medallion Architecture article

Driving Retail Information Architecture with the Databricks Medallion Architecture

How to organize and govern retail data — from POS to analytics — using the medallion architecture pattern on Databricks.

Read
Semantic Layer article

Building a Retail Semantic Layer with Unity Catalog Metric Views

How Databricks Unity Catalog Metric Views create a governed semantic layer that transforms complex retail data into consistent, business-ready insights.

Read
Databricks Genie article

Building a Retail Analytics Conversational UX with Databricks Genie

Genie allows COOs and business leaders to ask natural-language questions and receive instant answers grounded in governed data from Unity Catalog.

Read

Common Questions

Questions we hear from both data engineering and line-of-business teams.

Data modernization (migrating to Databricks, building pipelines, creating a governed semantic layer) creates the infrastructure foundation. Decision Intelligence is the layer that converts that foundation into operational value for line-of-business leaders — automated narrative answers to specific recurring questions, rather than more dashboards to interpret. Most organizations do the first and stop there. The ROI conversation changes significantly when you add the second layer, because the business benefit becomes visible to people outside the data team.

Decision Intelligence Agents run on top of your existing Databricks environment — they query your Unity Catalog tables and metric views through Databricks SQL, using your existing governance and access controls. If you are already on Databricks with Unity Catalog, the integration surface is clean: agents read governed data, produce narrative output, and deliver it to your existing reporting or notification workflows. We do not require you to change your data platform or your existing pipelines — the agents are additive.

Using the Knowledge Work Foundry, we generate a working agent configuration for a target workflow in hours. A production deployment typically takes 4–8 weeks from kickoff to go-live, depending on the complexity of the data integration surface and your existing Databricks setup. If your data foundation is already in good shape (Unity Catalog, governed metric views, reliable pipelines), that timeline compresses. The first working prototype can be demonstrated in the first meeting — your team interacts with it before leaving the room.

The highest-leverage targets are roles where recurring judgment decisions are currently gated behind high-cost execution work — meaning the decision-maker is capable of acting faster, but is limited by the time it takes to find and assemble context. In retail, that typically means regional operations managers (weekly performance synthesis), merchandising analysts (variance investigation, demand interpretation), and COO/VP Ops staff (leadership reporting and exception triage). Roles in supply chain (allocation, replenishment signals) and marketing (promotion analysis) are also high-value candidates depending on your org structure.

Expert services with our partners

Let's talk about your retail data platform.

Patterson Consulting helps retail organizations modernize their data infrastructure on Databricks and deploy the Decision Intelligence Agents that make that infrastructure visible to the line of business. Whether you're starting with data platform modernization or ready to add the Decision Intelligence layer, we'll meet you where you are.

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