Capability

Data, Analytics & AI Enablement

We help C-suite and senior executives build trusted data, governance, analytics, and decision systems that improve decisions and prepare the operation for responsible AI adoption.

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Peter Trosper Managing Principal, Data, Analytics & AI Enablement

Where we help

Data and AI in service of the operation, not the other way around.

We help C-suite and senior executives get value from their data by building systems designed to adapt and scale, so every operational decision is grounded in truth, not assumption. Then we help you put AI to work where it earns its keep: accelerating routine decisions and automating repetitive work.

Typical outcomes: unified visibility, faster decisions, less manual work, and more trust in data-driven operations.

What we do

Measurement strategy. KPI definitions, metric ownership, and the measures that tell leaders whether a process, platform, or change is working.
Data foundations. Data architecture, pipelines, governance, and documentation that create a single source of truth.
Analytics and dashboards. Reporting tailored to what leaders and operators need to decide and act.
Forecasting and planning models. Demand, labor, and capacity forecasting that planners trust and use.
Optimization. Route, slot, and inventory optimization, anomaly detection, and predictive maintenance.
AI in daily operations. Putting AI into business processes and workflows, with the data quality, governance, and privacy controls that make it safe to use, and tools your team can own.

Problems this capability solves

Where data and AI work makes the biggest difference

Improve Performance

Improve Operational Performance

See where cost and performance come from, and get the right metrics in front of the people who can act on them.

How we help Transform

Execute Complex Transformation

Build the data, governance, and decision systems a data-centric, automation-enabled operating model depends on.

How we help Build Capability

Build Sustainable Capability

Leave behind trusted data, clear metric ownership, and tools your own team can maintain and extend.

How we help

How we apply our model

From requirements to systems your team uses every day.

Set DirectionDefine what to measure
Start from the decisions the operation needs to make, then define the metrics, requirements, and architecture to support them.
Build SystemsBuild the foundation
Build the pipelines, models, dashboards, and AI tools, validated with operators so the numbers match what happens on the floor.
Execute & SustainDrive adoption
Put the tools into daily use, set clear ownership and governance, and hand over systems built for your team to own.

Representative engagements

Recent data and analytics work

Client names are kept confidential.

Planning redesign to stop facility closures

Client need: Improve Operational Performance: Facilities were closing repeatedly during critical delivery windows.
Capabilities: Supply Chain & Logistics, Data, Analytics & AI Enablement
What we built: Diagnosed the closures as a planning-system failure, then redesigned mid- and short-term planning processes and drove the supporting technology and process changes.
Outcome: Increased order capacity, improved customer experience, and reduced cost-to-serve.

Operating cadence for a new COO

Client need: Build Sustainable Capability: A newly appointed COO of a PE-backed company needed to accelerate execution against EBITDA priorities.
Capabilities: Leadership & Organizational Effectiveness, Data, Analytics & AI Enablement
What we built: Partnered with the COO to establish the operating cadence, management frameworks, and KPI architecture the business needed.
Outcome: Stronger accountability and faster execution against the company’s EBITDA priorities.

A national distributor’s move to data-centric, automated operations

Client need: Execute Complex Transformation: A national distributor was transitioning toward a data-centric, automation-enabled operating model.
Capabilities: Data, Analytics & AI Enablement, Operations & Manufacturing
What we built: Defined its data architecture, analytics organization, metric governance, and decision systems, and strengthened its automation evaluation, RFP, simulation, and maintenance-planning processes.
Outcome: A defined data, analytics, and decision foundation guiding the distributor’s shift to an automation-enabled operating model.

Capability leader

Led by a data leader who built analytics at Amazon scale.

Peter Trosper

Managing Principal, Data, Analytics & AI Enablement

Peter brings 20 years of data and analytics leadership, building trusted data foundations that enable AI tooling, self-service analytics, and faster, higher-quality decisions across global teams.

Before Cade Ops, at Amazon:

Directed teams building machine learning and rule-based coaching tools that reduced average handle time and improved associate performance.
Led a standardized, self-service source of truth for customer service metrics, creating the data foundation for AI tooling.
Built Amazon Shipping’s reporting infrastructure from scratch as Head of Business Intelligence.
Was part of the founding team that launched Fulfillment by Amazon.

Peter’s full profile

Insights