The Connected Commercial Planning Maturity Model: Where You are and What it’s Costing You
Sep 22, 20266 mins read
Most CPG organizations know their trade and marketing teams aren’t aligned. Fewer know exactly where they stand — or what it’s realistically costing them to stay there.
If you’ve spent time in CPG commercial planning, the friction is familiar. A trade promotion calendar built around retailer windows with no visibility into what the brand team is spending that same week. A marketing campaign driving consumers toward a product that isn’t on promotion — or isn’t on the shelf. Two organizations with adjacent goals, separate budgets, and no shared plan.
The structural reasons this disconnect exists — and what a truly connected operating model looks like — are explored in depth in Argano’s companion pieces, The $500 Billion Blind Spot and Connected Commercial Planning: The Next Operating Model for CPG. This piece takes a different cut: not the what or the why, but the where are you — and the path from here to there.
The gap between “siloed” and “optimized” isn’t a binary. It’s a maturity curve. And most organizations are somewhere in the middle, spending real money on the distance between where they are and where they could be.
Key takeaways
- The Maturity Curve: CPG commercial planning spans four stages—from spreadsheet-heavy Pre-Crawl to fully connected and optimized Run stages across trade, marketing, finance, and supply chain.
- The Cost of Disconnection: Fragmented planning leaves up to 72% of US promotions unprofitable and wastes 10-30% of marketing budgets, whereas connected planning lifts revenue up to 10%.
- AI Data Foundation: Advanced AI initiatives require harmonized data; moving to a shared commercial planning platform creates the structured architecture needed for scalable AI-driven optimization.
Four Stages of Commercial Planning Maturity
Pre-Crawl: Everything lives in spreadsheets.
Top-down budget allocations for both Trade Promotion Management (TPM) and Marketing Performance Management (MPM) are managed in Excel. Planning is manual, data is fragmented across files and inboxes, and anything resembling a unified view of commercial investment gets built fresh every time finance asks for it. The risk here isn’t just inefficiency. It’s invisibility — you can’t optimize what you can’t see.
Crawl: One side is systematized. The other still isn’t.
Many organizations have moved one discipline — usually TPM — onto a purpose-built platform, while MPM planning continues in spreadsheets. Or vice versa. The result is a new problem: a well-structured model on one side and unstructured data on the other, with a human being functioning as the integration layer between them. Running exports, reformatting data, trying to reconcile two versions of commercial reality that were never designed to meet.
Walk: Two models that communicate — without a human in the middle.
At this stage, both TPM and MPM are systematized on a shared platform, and those models are actively exchanging data. Promotion calendars and marketing campaign calendars are visible side by side. Budget positions are shared. Key variables — spend timing, account-level activity, expected lift — flow between models in real time. This is where meaningful experimentation becomes possible: what happens to foot traffic and margin when a trade promotion and a performance marketing campaign are coordinated in the same trade area?
Run: Trade, marketing, finance, and supply chain — connected.
The fully optimized state extends the planning connection into demand forecasting and supply chain. When TPM event data and MPM signals both inform inventory positioning, stock-out risks surface before they become service failures, and the entire S&OP process gains commercial P&L visibility it has never had before. The organization runs from a shared, forward-looking plan — not from backward-looking reports reconciled after the fact.
What the Distance Between Stages Actually Costs
This maturity gap has a real price tag. Nielsen data shows that 59% of promotions lose money globally — a number that climbs to 72% in the U.S. On the marketing side, 10 to 30% of budgets are estimated to be wasted. The Promotion Optimization Institute’s 2025 State of the Industry report found that 67% of CPG professionals describe the end-to-end promotional planning process as burdensome — and that burden is strategic, not just administrative.
When the planning layer governing both budgets is a web of spreadsheets, those numbers are very hard to move. Organizations that have shifted to connected commercial planning report top-line revenue increases of up to 10% and a minimum of 2x improvement in operational efficiency. Those aren’t marginal gains. They’re the kind of outcomes that restructure competitive position.
Why AI Makes This More Urgent, Not Less
The AI initiatives most CPG organizations are now funding — demand sensing, promotion optimization, dynamic pricing — all share a common dependency: structured, harmonized data. Gartner projects that 60% of AI projects without AI-ready data will be abandoned through 2026.
If your trade data and marketing data are living in separate systems with no shared schema and no unified financial model, your AI investments are building on an unstable foundation. Connected commercial planning isn’t just an efficiency play — it’s a data infrastructure decision. Moving TPM and MPM planning onto a shared, structured platform produces the data architecture that makes AI-driven optimization viable at scale. The organizations that move now are building a structural advantage that compounds with every planning cycle.
What Moving Actually Looks Like
The most common hesitation in this conversation is the assumption that connecting commercial planning requires a multi-year transformation program. That overstates the complexity. On a modern connected planning platform, individual models — TPM, MPM, demand planning — can typically be deployed in five to seven months, and they can be stood up in parallel rather than sequentially. You don’t have to choose which side to fix first.
Industry context matters here, too. A beverage company operating through three-tier distribution faces a materially different TPM environment than a direct-to-retail food manufacturer. The fastest-moving organizations aren’t starting from a blank sheet of paper — they’re working with partners who bring established patterns from analogous deployments and adapt them to the specifics of the business, including vertical-specific nuance in how promotions are structured, settled, and measured.
Where Do You Stand?
If you’re actively working through where your organization sits on this curve, Argano’s on-demand session on connected commercial planning walks through the full maturity model in depth — including a 12-question Data Agility Maturity Assessment you can use to benchmark your current state and identify where to focus next.
The planning infrastructure for most CPG organizations hasn’t been materially upgraded in decades. The technology to change that exists today. The question is whether the urgency is visible enough to act on it.
FAQs on connected commercial plannning
What are the four stages of the connected commercial planning maturity model?
They are Pre-Crawl (all spreadsheet-based), Crawl (one discipline systematized), Walk (models communicating without human intervention), and Run (fully connected across supply chain).
What characterizes the Pre-Crawl maturity stage in CPG planning?
Both TPM and MPM allocations are managed manually in Excel, resulting in fragmented data, manual rebuilds for finance requests, and complete invisibility of total investment.
What happens during the Walk stage of commercial planning maturity?
TPM and MPM are systematized on a shared platform, actively exchanging real-time variables like spend timing and account activity to enable coordinated multi-channel experimentation.
Why is connected commercial planning critical for successful AI adoption?
AI projects require clean, structured, and harmonized data. Unifying trade and marketing planning builds the foundational data architecture needed to prevent AI abandonment.
How long does it typically take to deploy modern connected planning models?
On a modern connected planning platform, individual models like TPM, MPM, and demand planning can be deployed in parallel within five to seven months rather than years.