— Our Methodologies
Frameworks & Methodologies
6
Frameworks Developed & refined
APPLIED
Methods refined through practical client work.
3
Manufacturing, construction and energy.
KPIs
Defined before delivery and reviewed in use.
Why This Matters
Structure turns strategy into decisions
When a transformation programme stalls, the problem is rarely a shortage of tools. It is usually unclear priorities, untested assumptions and no shared way to move from evidence to action.
Our frameworks make that path visible. They connect the business problem, workflow, data, technology choices, ownership and success measures—so leaders can decide what to do first, what to test and what must be true before scaling.
Repeatable Outcomes
Frameworks eliminate guesswork. The same methodology produces consistent results across industries, team sizes, and geographies.
Measurable Impact
Every framework includes built-in KPIs and success metrics. We measure what matters, not vanity metrics.
Adaptive by Design
Our frameworks are modular. They adapt to your organization's maturity, budget, and timeline without losing structural integrity.
Deep Dives
Frameworks Applied: Pillar Guides
These comprehensive guides demonstrate how our frameworks translate into actionable implementation strategies for specific technology domains.
- PREMIUM Guide
- PREMIUM Guide
- PREMIUM Guide
- PREMIUM Guide
- PREMIUM Guide
Explore Further
The Toolkit
6 Frameworks, 1 Philosophy
Each framework addresses a specific business challenge from AI adoption to brand transformation to platform selection. Together, they form a comprehensive consulting toolkit for organizations navigating digital transformation.
AI Strategy
The AI Governance Protocol
Map where AI helps and where it hurts empirically.
Most organisations adopt AI based on vendor promises or industry hype. They invest in tools without understanding which tasks AI improves and which it degrades. The result is wasted budget, frustrated teams and stalled adoption.
The Jagged Frontier Discovery Protocol is a five-step method for testing where AI adds value, where human judgement remains essential and where a combined approach works best. It replaces broad assumptions with task-level evidence.
Outputs include a prioritised task map, documented quality criteria and a shortlist of use cases ready for controlled validation.
KEY STEPS
- Task Inventory: Catalog every repeatable task across departments with frequency, effort, and business impact scores
- AI Experiment: Run controlled trials, same task, same quality bar with and without AI assistance
- Blind Quality Assessment: Independent reviewers score outputs without knowing which were AI-assisted
- Frontier Classification: Map each task to one of four zones: AI-dominant, Human-dominant, Collaborative, or Ambiguous
- Pattern Recognition: Identify organizational patterns that predict AI suitability across new tasks
APPLIED IN
AI Marketing
The AI Marketing Operating Model
Stop experimenting with tools. Start building a marketing system.
Manufacturing and construction teams often treat AI marketing as a collection of disconnected tools: a chatbot here, a content generator there. Without an operating model, those tools can create content silos, inconsistent messaging and limited visibility into pipeline impact.
The AI Marketing Operating Model connects five layers—data, AI processing, execution, channels and measurement—so campaigns and lead interactions can be managed as one system.
The output is a practical operating model with clear ownership, data inputs, channel workflows and agreed measures for testing what improves pipeline quality.
KEY STEPS
- Data Layer: CRM integration, web analytics, customer behavior signals, and industry benchmarks
- AI Processing Layer: Content generation, lead scoring, personalization engines, and predictive analytics
- Execution Layer: Campaign orchestration, content distribution, A/B testing, and workflow automation
- Channel Layer: Website, email, social, paid media, and sales enablement touchpoints
- Measurement Layer: Attribution modeling, ROI tracking, pipeline velocity, and continuous optimization
APPLIED IN
Brand Strategy
The 4-Layer Brand Framework
Strategy before architecture. Architecture before platform. Platform before performance.
Most brand transformations start with visual redesign—new logos, colours and websites. Without a strategic foundation, surface changes struggle to differentiate the offer, align teams or support commercial decisions.
The 4-Layer Brand Framework sequences positioning before information architecture, architecture before platform design, and platform before performance measurement.
Its output is a shared positioning system, content architecture, platform brief and measurement plan that teams can use to make consistent decisions.
KEY STEPS
- Strategy Layer: Market positioning, competitive differentiation, value proposition, and messaging hierarchy
- Architecture Layer: Brand system structure, content taxonomy, service line organization, and narrative frameworks
- Platform Layer: Digital presence, visual identity, design system, and communication channels
- Performance Layer: KPI definition, brand health tracking, conversion optimization, and continuous iteration
APPLIED IN
Data & Integration
The DATA Methodology
Discover. Assess. Transform. Activate.
Mid-sized manufacturers and construction firms often have operational data spread across ERP, CRM, spreadsheets and legacy databases. Replacing every source system is costly and disruptive.
The DATA Methodology maps critical flows, assesses quality and designs lightweight integration or orchestration layers around existing systems where appropriate.
A first phase produces prioritised integration opportunities, documented data-quality risks and an implementation sequence. Timing depends on access, source complexity and business scope.
KEY STEPS
- Discover: Map existing data sources, identify integration gaps, and catalog business-critical data flows
- Assess: Score data quality, quantify business impact of data silos, and prioritize integration opportunities
- Transform: Build lightweight orchestration layers that connect systems without replacing them
- Activate: Deploy AI-ready data pipelines that enable analytics, automation, and predictive capabilities
APPLIED IN
Digital Experience
The 8-Layer DXP Methodology
From content chaos to digital experience clarity in 8 structured layers.
Global organisations selecting digital experience platforms face hundreds of vendors, conflicting analyst views and internal stakeholders with competing priorities. A feature-led RFP can still end in a misaligned platform decision.
The 8-Layer DXP Methodology moves from business objectives and content operations through capabilities, architecture, cost and roadmap.
The output is a traceable decision pack: weighted requirements, architecture options, risks, cost assumptions and an implementation roadmap leaders can evaluate together.
Methodology Layers
- Business Objectives & KPI Map: Align platform selection with measurable business outcomes
- KPI & ROI Framework: Define success metrics before evaluating any vendor
- Content Operations Maturity: Assess current-state capabilities and gaps
- Global-to-Local Operating Model: Design governance for multi-market content operations
- DXP Capability Mapping: Map current vs. future-state platform requirements
- Prioritization Framework: Score and rank requirements by business impact and feasibility
- Architecture Options Analysis: Evaluate suite vs. composable vs. hybrid approaches
- Implementation Roadmap: Multi-phase plan with cost estimation and risk mitigation
APPLIED IN
Consulting Delivery
The 4-Phase Engagement Model
Discovery. Analysis. Design. Delivery. Every engagement, every time.
Consulting engagements lose momentum when scope, evidence, ownership and decision rights are unclear. The result is avoidable rework, shifting expectations and recommendations that are difficult to implement.
The 4-Phase Engagement Model keeps discovery before analysis, analysis before design and design before delivery. Deliverables and timing are then scaled to the client’s decision, available evidence and implementation context.
Each phase ends with a decision gate so assumptions, gaps, owners and the next commitment remain explicit.
KEY STEPS
- Phase 1: Discovery & Assessment - Stakeholder interviews, data collection, current-state mapping, and objective alignment (Weeks 1–3)
- Phase 2: Analysis & Benchmarking - Gap analysis, competitive benchmarking, opportunity scoring, and risk assessment (Weeks 4–6)
- Phase 3: Solution Design - Architecture design, vendor evaluation, prototype development, and business case modeling (Weeks 7–9)
- Phase 4: Executive Documentation & Roadmap - Board-ready deliverables, implementation roadmap, cost model, and governance framework (Weeks 10–12)
APPLIED IN
From benchmark to a scoped AI pilot
A typical first phase can produce prioritised opportunities in 4–6 weeks and a scoped pilot in around 60 days, subject to data readiness, integration complexity and stakeholder availability.
B
Benchmark
Weeks 1-2
* Assess processes
* Data readiness check
* Define success KPIs
Deliverables
AI Readiness Report
U
Uncover
Weeks 3-4
* Identify opportunities
* Prioritize by ROI
* Map workflows
Deliverables
Opportunity Roadmap
I
Implement
Weeks 5-10
* Deploy POC
* Build MVP
* System integration
Deliverables
Working Solution
L
Learn
Ongoing
* Monitor performance
* Optimize models
* Refine workflows
Deliverables
Continuous Improvement
T
Transform
Ongoing
* Scale across units
* Expand use cases
* Build capabilities
Deliverables
Enterprise Scale
Our Philosophy
Every Engagement starts with a business problem, not a technology solution.
Redex Consulting Methodology Principle
Industry Application
Frameworks in Action
Our frameworks are industry-agnostic by design but industry-specific in application. Here is how they map to the sectors we serve.
Framework
Manufacturing
Construction
Energy
AI Strategy
AI Marketing
Brand Strategy
DATA
DXP
Consulting Delivery
Related Services
NExt Step
Every Project Starts with a Conversation
Whether you are evaluating AI readiness, selecting a digital platform, or transforming your brand, the first step is understanding where you are today. We will help you identify which framework applies to your situation and what measurable outcomes you can expect.