SoloHarness

Consultants · Enterprise and independent consulting teams

Turn interviews into evidence,
and turn proposals into action.

We provide AI transformation consulting, training, and ongoing implementation support for consultants and consulting teams. Around your delivery process, we map out the professional capabilities AI can enhance, connecting research, analysis, solution validation, and action tracking. You get a clear improvement roadmap, technology choices, and ongoing implementation support.

Talk about your industry and AI transformationView the six delivery milestones and specific tasks ↓

Complete consulting delivery value flow

First understand how a consulting engagement moves from issue to action along six delivery nodes, then see how interview evidence plays a role within it.

From customer issues to sustained action

Six nodes connecting the complete consulting delivery.

Expand each node to see work inputs, the three tasks, technical support, professional confirmation, and handoff conditions.

Current example: Steps 1–3 · Goal confirmation → Research → Hypothesis validation

"For the same order, why do we always have to ask again during handover?"

Original words → process and exception records
→ Verifiable explanation → Pilot decision

  1. After the interview:Code the transcript by process step and role. The consultant reviews the original statements and checks routine practices and exceptions with frontline staff.
  2. During analysis:Compare handover records against data, have the model organize candidate causes, and use scripts to check definitions, gaps and anomalies.
  3. Form a judgment:The consultant checks counterexamples and alternative explanations, defines validation evidence, and gives the solution choice a basis.

The three-way relationship within the same job

Business roadmap, professional capability and technology
Mutually reinforcing.

Research milestones require on-site understanding, source verification and data analysis; these capabilities also serve hypothesis validation and results reporting. Transcription, retrieval, models and scripts are combined by task, with the consultant confirming the business context and conclusions.

01Consulting delivery milestones

Confirm client issues and objectives

Expand tasks +

Get the customer and consultant to align on the topics to be answered, the boundaries and the success criteria.

Work inputs · Customer needs, verbatim interview quotes, business goals and project constraints

1.1

Interview goals and constraints

Reusable capabilities
Listening, stakeholder assessment
AI technology and human confirmation
Voice transcription and model classification bind the original words to objectives, constraints and disagreements; the consultant reviews the original words and confirms the requirements with the relevant parties, listing unconfirmed assumptions as items to be verified
Deliverables
Topic summary, list of items to confirm
Quality goals
Objectives and disagreements have a documented basis
Efficiency goals
Reduce post-meeting organizing
1.2

Define scope and metric criteria

Reusable capabilities
Scope control, metric definition
AI technology and human confirmation
The model identifies conflicting definitions and criteria; the consultant and client confirm the scope and data availability
Deliverables
Scope table, metrics dictionary
Quality goals
Reduce ambiguity
Efficiency goals
Reduce rework
1.3

Define project milestones and decision gates

Reusable capabilities
Project planning, validation design
AI technology and human confirmation
The model generates dependencies and evidence requirements, the consultant confirms owners and return conditions
Deliverables
Plan, stage decision checklist
Quality goals
Clear conditions for progression
Efficiency goals
Reduce plan orchestration

Advancement and handover · After the customer confirms the topics, metric definitions, owners and stage decision criteria, proceed to research.

02Consulting delivery milestones

Current state and data research

Expand tasks +

Establish an analytical foundation with clear sources, consistent applicable definitions and criteria, and close alignment with actual operations.

Work inputs · Documents approved for use, business spreadsheets, field interviews and handover records

2.1

Collect process and business materials

Reusable capabilities
Source verification, permission management
AI technology and human confirmation
The document parser reads documents and spreadsheets, and the model extracts sources, versions, time ranges and material topics. The consultant confirms authorization, confidentiality scope and gaps.
Deliverables
Material list, permissions, and gap records
Quality goals
Transparent sourcing
Efficiency goals
Reduce repeated requests
2.2

Record actual operations and handover exceptions

Reusable capabilities
On-site understanding, process observation
AI technology and human confirmation
Transcription is coded by step and role; consultants verify norms and exceptions with frontline staff
Deliverables
Process map, process improvement opportunity table
Quality goals
Clear gap between policy and practice
Efficiency goals
Reduce manual coding
2.3

Check data quality and comparability

Reusable capabilities
Data analysis, applicable definitions and criteria
AI technology and human confirmation
The script checks for missing, duplicate and anomalous entries and time ranges; the consultant confirms exclusion rules and sample representativeness
Deliverables
Quality report, baseline set
Quality goals
Analysis basis is reproducible
Efficiency goals
Reduce cleanup rework

Advancement and handover · After source materials, sample rules and metric definitions are verified, they enter structured analysis.

03Consulting delivery milestones

Problem structuring and hypotheses

Expand tasks +

Organize field observations into verifiable explanations and clarify analysis priorities.

Work inputs · Verified interviews, baseline data, process and exception records

3.1

Organize phenomena, impacts, candidate causes, and relationships into a problem tree

Reusable capabilities
Problem structuring, causal reasoning
AI technology and human confirmation
The model generates candidate maps based on verified interviews and data with sources attached, marking observed facts, correlations and testable causal hypotheses separately; the consultant checks symptom/cause distinctions, counterexamples and alternative explanations
Deliverables
Issue tree, impact chain, source index
Quality goals
Reasoning chains and assumption states are clearer
Efficiency goals
Reduce organizing and reworking
3.2

Raise key hypotheses and define the evidence needed to support or refute them

Reusable capabilities
Hypothesis reasoning, research design
AI technology and human confirmation
The model converts the issue tree into falsifiable hypotheses, judgment criteria and analysis methods; the consultant confirms verifiability, business context and priorities
Deliverables
Assumption list, validation matrix, supplementary plan
Quality goals
Analysis is more verifiable
Efficiency goals
Reduce aimless analysis
3.3

Assess issue priority, impact, feasibility and dependencies

Reusable capabilities
Priority judgment, value reasoning
AI technology and human confirmation
The model generates a comparison table based on confirmed metrics and constraints; rule scripts calculate scores and retain inputs; the consultant confirms weights, data limitations, estimate ranges and ranking
Deliverables
Priority matrix, dependency table
Quality goals
More explainable evidence
Efficiency goals
Reduce repeated comparisons

Advancement and handover · After key assumptions, judgment criteria and priorities are confirmed, move into co-creating the solution.

04Consulting delivery milestones

Co-create the Solution

Expand tasks +

Jointly choose an executable plan and lock in responsibilities, resources and the path forward.

Work inputs · Issue tree, validation matrix, objectives and resource constraints

4.1

Organizational managers and frontline staff co-create processes, mechanisms, tools or organizational options

Reusable capabilities
Co-creation facilitation, solution design
AI technology and human confirmation
The model generates the agenda, solution cards and open questions based on research and the assumptions list; transcription tools record disagreements; the consultant facilitates on site and confirms understanding and constraints
Deliverables
Co-creation records, solution cards, decision checklists
Quality goals
The solution is closer to the front line
Efficiency goals
Reduce post-meeting reconstruction
4.2

Compare the impact of options on goals, processes, resources, risks and acceptance

Reusable capabilities
Solution evaluation, trade-off analysis
AI technology and human confirmation
The model generates comparison tables, and the calculation script runs scenario calculations based on cost/scheduling assumptions with labeled sources, distinguishing measured values, estimates and forecast results; the consultant confirms inputs, weights and real-world constraints
Deliverables
Comparison tables, calculation sheets, recommended options
Quality goals
Trade-offs and forecast assumptions are more transparent
Efficiency goals
Reduce repetitive production
4.3

Design target processes, responsibilities, metrics, steps, and risk responses

Reusable capabilities
Process design, implementation planning
AI technology and human confirmation
The model converts the selected solution into a process diagram, responsibility assignment matrix, metric cards and risk register, and rule-checks for missing responsibilities and dependency conflicts; consultants and owners confirm resources, permissions and escalation paths
Deliverables
Target process, responsibility matrix, roadmap
Quality goals
More complete execution conditions
Efficiency goals
Reduce the work of filling in task dependencies

Advancement and handover · Enter the pilot after solution trade-offs, execution responsibilities and resources are confirmed.

05Consulting delivery milestones

Pilot and validation

Expand tasks +

Use execution records and outcome comparisons to support decisions to retain, adjust, stop, or expand.

Work inputs · Approved plan, metrics dictionary, data collection permissions and pilot baseline

5.1

Select pilot scope, targets, baseline, duration, participants and metrics

Reusable capabilities
Validation design, risk control
AI technology and human confirmation
The model generates the pilot design and collection tasks based on the validation matrix, and scripts check baseline definitions and criteria and sampling completeness; the consultant confirms representativeness, usable controls, data permissions and stop conditions
Deliverables
Pilot plan, baseline, collection plan
Quality goals
Clear validation boundaries
Efficiency goals
Reduce preparation time
5.2

Track execution, collect results, deviations, feedback and unexpected impacts

Reusable capabilities
On-site observation, data analysis, anomaly identification
AI technology and human confirmation
Data connectors aggregate systems and spreadsheets per authorization, rule scripts flag anomalies, models organize feedback and preserve sources; consultants verify causes, distinguishing execution deviations, solution issues, and testable explanations
Deliverables
Pilot log, result set, feedback list
Quality goals
More complete evidence
Efficiency goals
Reduce status summaries
5.3

Based on evidence, decide to retain, adjust, stop or expand the pilot

Reusable capabilities
Evidence judgment, decision communication
AI technology and human confirmation
The calculation script generates result comparisons and sensitivity analysis according to the confirmed definitions and criteria, and the model organizes conclusions and the evidence index; the consultant reviews samples, comparisons, limitations and alternative explanations, clarifies the scope of conclusions supported by the data, and leads the responsible parties to make the stage decision
Deliverables
Validation report, stage decision, rollout conditions
Quality goals
Decisions bound to evidence
Efficiency goals
Reduce manual calculations

Advancement and handover · The responsible person makes decisions based on evidence, clarifies the conditions for adjustment or rollout, and then moves into delivery.

06Consulting delivery milestones

Results reporting and ongoing implementation support

Expand tasks +

Hand off conclusions and recommendations as actions the customer can keep driving forward.

Work inputs · Validation reports, approved plans, execution status and customer feedback

6.1

Form conclusions, evidence chains, recommendations and management materials

Reusable capabilities
Deliverable presentation, audience adaptation
AI technology and human confirmation
The model generates a conclusion–evidence–impact–recommendation structure, and the chart script reads the verified data; the consultant checks the sources, calculations and presentation boundaries, separately labeling observed facts, verified conclusions, unverified assumptions and recommendations.
Deliverables
Conclusion report, briefing, appendix
Quality goals
Conclusion evidence and applicable scope are clearer
Efficiency goals
Reduce version orchestration
6.2

Break recommendations into actions, owners, deadlines, resources, dependencies and checkpoints

Reusable capabilities
Implementation planning and handover of responsibilities
AI technology and human confirmation
The model turns the approved plan into tasks and dependencies; the workflow tool sets reminders and status fields according to confirmed rules; the consultant confirms commitments, resources and escalation conditions with the customer
Deliverables
Action plan, responsibility ledger, milestones
Quality goals
Clearer execution accountability
Efficiency goals
Reduce post-meeting task breakdown
6.3

Review execution data, handle deviations, update methods, and complete handover

Reusable capabilities
Change implementation support, continuous improvement
AI technology and human confirmation
Data connectors aggregate authorized status data and metrics; the model organizes feedback, exceptions and the review agenda. The consultant checks causes against execution records, confirms adjustments, escalation and acceptance criteria, and completes the handover
Deliverables
Review records, adjustment checklist, handover package
Quality goals
Open items and experience visible
Efficiency goals
Reduce periodic summaries

Advancement and handover · The action owner receives tasks and resources, continuously reviews against checkpoints and completes acceptance handover.

Start from your actual business

Turn the next consulting delivery into sustainable capability.

Starting from project goals, information sources and existing ways of working, identify capability enhancement opportunities, choose suitable AI and system connections, and continuously check output quality and execution progress.

Talk about your industry and AI transformation

Contact Andy

Talk about your industry and AI transformation

Add me on WeChat and let's talk about the one piece of work you want to improve first.

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