Digital Transformation Valuation Metrics Framework

Applied Delphi Review System

A Kratos-style research interface for expert validation of AI and automation training valuation metrics.

What this site is for

DTVMF supports expert review of 28 candidate metrics for valuing digital transformation, AI implementation, and automation-related training. The goal is not to ask whether a metric “sounds good.” The goal is to determine whether the metric works when an organization has to collect data, defend the formula, connect the result to a named income statement line, and translate the outcome into firm value.

The review follows the study’s modified Delphi logic: Round 1 emphasizes qualitative critique; Rounds 2 and 3 use structured ratings for content validity, feasibility, formula clarity, income statement accuracy, auditability, and sector applicability.

Three-stage value chain

1
Operational outcome
What changes in actual work: time, defects, adoption, cycle variability, margin, working capital, or innovation.
2
Income statement effect
Where the improvement lands: COGS, SG&A, operating income, revenue, working capital, legal reserves, or human capital disclosure.
3
Firm value translation
Whether the improvement can be translated to NOPLAT, FCFF, ROIC, EVA, WACC-adjusted value, or another defensible valuation mechanism.

How experts should judge each metric

For each item, act as though a CFO, operations director, HRD leader, and implementation analyst will all challenge the metric. A strong metric should have a clear formula, plausible data source, defensible financial linkage, and enough auditability to survive organizational scrutiny.

RelevanceFeasibilityFormula clarityLine accuracyAuditabilitySector fit

Recommended completion process

1
Select a Delphi round.
Round 1 privileges qualitative critique. Round 2 and 3 ratings support CVI-style analysis and consensus review.
2
Review metrics as applied measurement objects.
Use the formula, data source, income statement line, benchmark, and firm value logic together. Do not rate from the metric name alone.
3
Write revision guidance wherever the metric is weak.
The most valuable comments identify formula problems, missing data constraints, sector limitations, and financial linkages that would not survive audit.
Step 1 of 5

Consent & Expert Profile

Identify the panelist’s expertise so responses can be interpreted by domain.

Expert profile

Study agreement

Purpose

This study validates a Digital Transformation Valuation Metrics Framework through expert review. Experts evaluate metric relevance, feasibility, formula clarity, income statement linkage, auditability, and sector applicability.

Participation

Participation involves reviewing 28 candidate metrics and providing structured ratings and open comments. Participation is voluntary and may be discontinued at any time.

Confidentiality

For the production study, this section should be replaced with the final IRB-approved consent language and data storage procedures.

Enter your name, select primary expertise, and check consent to continue.
Step 2 of 5

Implementation Context

Anchor the review in an applied setting rather than abstract metric preference.

Applied scenario

Preparation checklist for expert review

1
Use your domain expertise. Judge whether the metric is plausible in the systems and reporting environments you know.
2
Look for audit problems. Flag formulas that produce attractive numbers but cannot be defended with available organizational data.
3
Separate relevance from feasibility. Some metrics are conceptually strong but too difficult to implement without major data infrastructure.
Step 3 of 5

Metric Review

Rate each metric and provide applied revision guidance. Progress saves automatically in this browser.
Started
0
Complete ratings
0
Mean relevance
—
Round
1
0 of 28 started
Step 4 of 5

Instrument Feedback

This section evaluates the DTVMF instrument and web workflow, not a specific metric.

Usability and methodology feedback

Step 5 of 5

Review & Export

Download expert response data and inspect prototype admin summaries.

Download files

Use these files for pilot testing. A production version should send these records to a database tied to tokenized expert invitations.

Prototype admin summary

Demo data approximates how panel-level CVI and feasibility review would appear after multiple experts respond.

0Current response records
0%Current completion
n/aMean demo I-CVI
0Demo flagged items
#MetricLevelI-CVIFeasibilityStatus