JPS Consulting

Decision Intelligence, AI Strategy & Go-to-Market Architecture

Most organisations do not have a marketing problem. They have a decision problem upstream.

The market reacts to decisions, not intentions.

Decision Architecture

I work at leadership level on positioning, go-to-market and growth decisions when existing revenue logic no longer holds.

Typical context:

  • Legacy channels have structurally broken down
  • The offering has outgrown product-led or campaign-led logic
  • Sales cycles are long, co-development driven, and politically complex
  • Technology, AI or platform capability is ahead of its commercial articulation

This is not execution support. It is decision architecture under complexity.

Marketing Failure Originates Upstream

Marketing is usually where decision failure becomes visible, not where it originates.

The failure chain is predictable:

Signals
Data, market behaviour, customer feedback

→ Interpretation
Assumptions, narratives, bias, internal politics

→ Decisions
Priorities, trade-offs, timing, risk tolerance

→ Execution
Messaging, offers, channels

→ Market Response
Attention, trust, traction

Nothing here is broken individually. The system is.

Observable Failure Patterns

It Looks Like a Marketing Problem

Campaigns do not convert. Messaging changes, performance does not. No one agrees why.

Usually not an execution issue.

It Looks Like a Data Problem

Dashboards exist. Decisions still feel political. Numbers conflict. Confidence remains low.

Usually an interpretation problem.

It Looks Like a Strategy Problem

Direction keeps shifting. Execution fragments. Priorities are debated, not decided.

Usually a system design problem.

These are not execution failures. They are decision failures.

Operating Position

I operate inside the decision layer above marketing, sales and growth execution.

The objective is not more activity. The objective is coherent, defensible decisions about:

  • Visibility
  • Positioning
  • Portfolio structure
  • Go-to-market logic

So execution stops compensating for unclear thinking.

Current & Recent Work (Indicative)

Marketing and go-to-market advisory for a European technology hub transitioning away from an OEM-driven partnership model.

Context:

  • Over a decade of OEM-led revenue
  • Highly complex, non-productised technology and AI portfolio
  • Long-cycle B2B sales and co-development environments

Focus of work:

  • Portfolio structuring
  • Market-facing positioning
  • Go-to-market decision logic

Conducted under NDA.

The Economic Model I Am Developing

The model I am developing is not monetised through volume-based demand generation. It is monetised through participation in verified economic upside.

Its commercial logic is structurally different from traditional marketing-led growth.

The model operates as an additional decision-evidence layer on top of an organisation’s existing marketing and sales operation. It does not replace tools, platforms, teams or execution capacity.

Clients do not pay to “use” the model. They pay because it enables decisions that would otherwise not be made or prevents decisions that would otherwise destroy value.

Revenue does not originate from selling software, licences, retainers or time-based services. Revenue originates from a predefined share of incremental value that becomes visible and attributable once decision rationality is made explicit and enforceable.

In early engagements, this structure removes the need for upfront capital allocation:

  • No demand generation spend
  • No brand building requirement
  • No customer acquisition at scale

Each engagement is economically self-contained and justified by the value it exposes.

Early-stage costs are limited to:

  • Operational maintenance of the framework
  • Governance, validation and auditability of decision evidence

Adoption occurs top-down, where decision accountability already exists and where economic upside can be contractually shared.

As a result, monetisation follows a participation model, not a promotion model:

  • Low fixed cost
  • No growth-at-all-costs assumption
  • Revenue proportional to realised, defensible value

Growth is constrained by decision relevance, not by reach. Revenue is constrained by verified value creation, not by adoption volume.

The absence of large marketing spend is not a limitation of the model. It is a direct consequence of its structure.

Executive Context

I typically work directly with:

  • Founders
  • CEOs
  • Executive teams

Especially when existing sales logic no longer supports the complexity of what is being sold.

Explicit Exclusions

I do not:

  • Procure development agencies or software vendors
  • Manage implementation teams
  • Run campaigns or growth experiments
  • Sell marketing services

Engagement Models

Growth System Diagnostic

Purpose
Expose where value is leaking, where potential is hidden, and what must be fixed first.

Typical investment
€4,000 – €8,000 (scope dependent)

Growth System Blueprint

Purpose
Design and document a complete growth system aligning marketing, sales and data under one decision logic.

Typical investment
€12,000 – €25,000 (often split across milestones)

Fractional Growth Architect

Purpose
Operate the blueprint with leadership cadence, prioritisation and governance.

Typical investment
€3,000 – €8,000 / month

Decision Framing

We can examine your decision system together and identify where distortions enter before they reach the market.

This is not a sales call. It is a structured diagnostic conversation.

→ Email me

JPS Consulting
Gibraltar – Spain