Technology Portfolio Management (TPM) Best Practices - Start with spreadsheets and AI before investing in dedicated TPM platforms
Technology Portfolio Management (TPM) Best Practices
Start with spreadsheets and AI before investing in dedicated TPM platforms
Overview
The governance capability required for an effective TPM program in its early stages is available from well-structured, consistently maintained spreadsheets analyzed with AI tools, at a fraction of the cost and complexity of a dedicated TPM platform implementation. Organizations that recognize this consistently build more effective early-stage TPM programs than those that invest in platform implementation before the governance framework is mature enough to populate and use the platform effectively. The investment in platform implementation is justified when the governance complexity genuinely exceeds what spreadsheet-based governance can support — which typically means when the Technologies Inventory family has grown to a scale that manual maintenance creates data quality problems, when the number of governance workflows has grown to a volume that spreadsheet tracking creates coordination failures, or when the reporting requirements have grown to a sophistication that spreadsheet-generated reports are no longer adequate.
Best Practice
Begin the Technologies Inventory family with versioned spreadsheets, one per inventory type, structured according to the IF4IT taxonomy and populated with the minimum viable data set for each inventory type. Use AI tools to perform the analytical work that would otherwise require dedicated TPM platform analytics: load the Technologies Inventory spreadsheets into a capable AI model alongside the Applications Inventory and other relevant inventory data, and use natural language queries to perform Technology Spread analysis, cross-inventory impact assessment, rationalization scoring, and portfolio health measurement. A well-structured, consistently maintained spreadsheet-based inventory loaded into AI produces governance insights that are substantially more valuable than the outputs of a poorly governed, inconsistently maintained platform-based inventory. Continue the spreadsheet-and-AI approach until the complexity genuinely justifies platform investment, and use the experience gained during the spreadsheet phase to define the platform requirements with the specificity and accuracy that only governance experience can produce.
Benefit(s)
Starting with spreadsheets and AI produces a governance foundation that is immediately actionable, inexpensive to establish, and informative about the platform requirements that will eventually justify the platform investment. The governance intelligence produced during the spreadsheet phase — the technology assessments, the rationalization priorities, the financial quantifications, the risk findings — delivers organizational value from the first governance cycle rather than waiting for a platform implementation to complete. The AI analysis capability that modern AI tools provide makes the spreadsheet phase substantially more powerful than the spreadsheet-only approaches of previous generations, narrowing the capability gap between spreadsheet-based and platform-based governance to the point where the breakeven complexity for platform investment is higher than most organizations assume.
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