Use precise financial figures for technology costs where available — orders of magnitude where not - Technology Portfolio Management (TPM) Best Practices

Use precise financial figures for technology costs where available — orders of magnitude where not

(Chapter 130 of Technology Portfolio Management (TPM) Best Practices)

Executive Summary: Chapter Overview

IF4IT

The Bottom Line

TPM programs frequently stall on financial data collection because precise figures are not available for every technology, and the program waits for accounting-grade data before publishing anything. Organizations should use precise figures where available and disciplined Order-of-Magnitude estimates where not, recognizing that partial financial visibility supports portfolio decisions that zero financial visibility could not.

Core Concepts

Concept	Definition & Strategic Role
Precise vs. Order-of-Magnitude Figures	The pragmatic approach of using precise financial figures for technologies where accounting-grade data exists and disciplined OoM — small, medium, large, extra-large ranges — for technologies where precise data cannot be produced without disproportionate effort.
Documented Uncertainty	The practice of recording financial data with explicit precision indicators — precise, estimated, OoM — so downstream analysis can distinguish confident numbers from bounded estimates.

Quick Q&A

Question: Why not wait for precise figures across the entire Technologies Inventory?

Answer: Waiting produces zero portfolio value, and the precise figures may never arrive — operational costs allocated across many technologies and legacy contracts with obscure cost breakdowns often cannot be resolved to per-technology precision at acceptable effort.

Question: How do OoM estimates support real portfolio decisions?

Answer: By making relative comparisons possible even where absolute precision is not. Rationalization prioritization typically depends on relative cost, not absolute cost — knowing which technologies are large-cost and which are small-cost is sufficient for most prioritization.

Overview

TPM financial analysis is frequently delayed because the precise financial data required for exact analysis is unavailable or prohibitively expensive to collect with sufficient precision for every technology. Teams wait for perfect data before producing any financial analysis, and the wait becomes indefinite because perfect data is never fully achievable in complex enterprise environments.

Best Practice

Adopt a practical, explicitly stated approach to technology financial analysis that uses precise figures where they are genuinely available from reliable financial systems and uses OoM estimates where they are not. Present OoM estimates explicitly as such, with the reasoning behind the estimate range and the confidence level clearly communicated alongside the figure. Invest in improving financial precision only for the specific technologies where more precise figures would change a specific decision currently being made. This pairs directly with the general Order-of-Magnitude Estimation practice already established for technology cost and complexity scoring.

Benefit(s)

Accepting and clearly labeling OoM estimates as valid portfolio financial data produces financial analysis that is available when decisions need to be made rather than after they have already been committed under financial uncertainty. Investment in financial data precision is directed to the specific technologies and decisions where it will change outcomes.

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