Addressing Model Fallout and Data Quality at All Levels of the TBM Model
Even the most carefully designed TBM model will experience fallout. Fallout occurs when costs or resources cannot be fully mapped through the model and end up stranded in categories like “Unmapped,” “Unassigned,” or “Other.” These gaps reduce confidence in reporting, limit transparency, and make it harder to answer basic questions such as “What are we really spending on storage?” or “How much of this service is consumed by Business Unit A versus Business Unit B?”
It is important to understand that fallout is not a symptom of low maturity. Organizations at every stage of TBM adoption—whether just getting started with Cost Pools or fully modeling Solutions and Consumers—will encounter unmapped costs and data quality challenges. The difference lies in how consistently and effectively fallout is monitored, investigated, and resolved.
This page provides guidance for identifying and addressing fallout across all layers of the TBM model—from Cost Pools and Resource Towers to Solutions and Consumers. You will learn how to:
- Recognize the common ways fallout appears in your model.
- Apply systematic checks to identify and quantify unmapped spend.
- Remediate gaps by improving mappings, metadata, and governance.
- Treat fallout management as an ongoing operational discipline rather than a one-time project.
By proactively addressing fallout and data quality, you ensure that your TBM model delivers credible, decision-ready insights for finance, technology, and business stakeholders.
Common Sources of Fallout and Data Quality Issues
Fallout in a TBM model almost always traces back to gaps in data, mappings, or governance. Recognizing where and why fallout occurs is the first step toward fixing it. While every organization’s systems and processes are different, the following categories represent the most frequent causes of unmapped or low-quality data in TBM models.
Financial Data Issues
- Unmapped accounts – Chart of Accounts entries or GL lines not linked to a Cost Pool or Sub-Pool.
- Vague account descriptions – Descriptions like “Miscellaneous IT” that resist precise mapping.
- Missing budget identifiers – Budget records lacking a unique ID, preventing alignment with actuals.
- Stale mappings – Accounts reused for new purposes but not revalidated against the TBM taxonomy.
Resource Tower and Infrastructure Data Issues
- Unassigned resources – Servers, databases, or devices in CMDB or cloud billing data with no Tower/Sub-Tower tag.
- Tagging gaps – Cloud resources without cost allocation tags (e.g., environment, business unit).
- Duplicate or conflicting entries – Resources listed in multiple systems with inconsistent attributes.
- Unclear ownership – Assets not linked to a department or cost center, making attribution difficult.
Solution and Offering Data Issues
- No service or solution catalog – Without a baseline catalog, costs cannot be attributed to defined solutions.
- Undefined offerings – Organizations skipping the offering element of the Solutions layer, limiting granularity.
- Partial allocations – Only some sub-towers (e.g., servers) are mapped to solutions, leaving others stranded.
- Overlapping definitions – Different teams defining the same “solution” differently, leading to inconsistent attribution.
Allocation and Attribution Issues
- Weak cost drivers – Allocation logic missing appropriate drivers (e.g., CPU hours, ticket counts).
- Over-reliance on flat splits – “50/50” or similar allocations that don’t reflect actual consumption.
- Driver data missing or incomplete – Metrics like storage GBs or user counts not available across all towers.
- No traceability – Allocations applied without documenting the method, confidence, or assumptions.
Process and Governance Issues
- Lack of review cadence – Fallout grows unnoticed if mappings aren’t regularly reviewed.
- Siloed accountability – Finance, IT, and TBM teams each assume the other owns fallout remediation.
- Inconsistent versioning – Old mapping files or ad-hoc changes lead to “model drift.”
- No QA reporting – Fallout is not measured or surfaced to stakeholders until it undermines trust in reports.
Quick Tip: Fallout is not a one-time clean-up exercise. Every system change, new cloud account, or business restructuring can introduce new unmapped items. The goal is to build repeatable detection and remediation practices into your TBM operating rhythm.
Understanding the common sources of fallout is only the beginning. To address it effectively, you need to evaluate fallout at each layer of the TBM model—Cost Pools, Resource Towers, and Solutions. Each layer introduces its own data challenges, and fallout may appear differently depending on whether you are categorizing financials, allocating infrastructure, or mapping to business-facing solutions.
The sections that follow provide layer-by-layer guidance on how fallout emerges, what it means for your model, and how to remediate it.
Fallout and Data Quality at the Cost Pool Layer
At the foundation of the TBM model, Cost Pools and Sub-Pools provide the first standardized categorization of IT spend. They serve as the entry point into the TBM Taxonomy and ensure that financial data is consistently represented before being allocated to Resource Towers, Solutions, or Consumers. Fallout at this layer usually stems from unmapped or poorly described financial accounts. Even small levels of fallout here can ripple upward—undermining Resource Tower allocations, obscuring IT Finance reporting, and eroding stakeholder trust.
Common Types of Fallout
Fallout at the Cost Pool layer is most often a result of gaps or misalignments in the mapping of General Ledger (GL) accounts or budget lines. When accounts are not fully understood or consistently tagged, fallout emerges.
- Unmapped GL or budget lines – Accounts or budget entries not tied to a Cost Pool/Sub-Pool.
- Misclassified entries – Costs mapped to the wrong Cost Pool due to vague account names (e.g., “Software” could mean licenses or SaaS).
- Incomplete CapEx/OpEx tagging – Missing indicators that prevent accurate financial treatment and reporting.
- Residual “miscellaneous” spend – Catch-all accounts left unmapped or lumped together, which can be disproportionately high in dollar value.
Risks of Ignoring Fallout at This Layer
Because Cost Pools form the structural base of the TBM model, fallout here has a magnified impact as costs flow upward. Ignoring fallout at this stage creates foundational weaknesses that propagate through the entire model.
- Reporting distortion – Total IT spend by category becomes unreliable if even small portions of spend are unclassified or misclassified.
- Blocked allocations – Unmapped costs cannot flow into Resource Towers, Solutions, or Consumer views, leaving gaps in downstream reporting.
- Lost transparency – Stakeholders lose trust in the TBM model when they encounter “miscellaneous” categories or unexplained gaps in dashboards.
Recommended Detection Practices
Detecting fallout at the Cost Pool layer requires proactive monitoring and the use of structured validation routines. Organizations should implement systematic ways to surface missing or questionable mappings.
- QA dashboards – Build reports to surface any GL or budget lines without a Cost Pool assignment so issues can be identified in near real-time.
- Threshold monitoring – Track unmapped spend as a percentage of total IT financials, and set an acceptable threshold (e.g., less than 1%). Crossing that threshold should trigger review and remediation.
- Comparative analysis – Compare current mappings to prior periods to spot drift, sudden increases in unmapped spend, or new accounts introduced without classification.
Remediation Approaches
Once fallout is detected, remediation requires applying consistent, repeatable methods to reclassify accounts accurately. These methods should be documented and auditable for future cycles.
Keyword Matching
Apply keyword lookups against account descriptions to suggest mappings. For example, words like “contractor,” “license,” or “hosting” can guide Sub-Pool assignments. Always document the source of the mapping and your confidence in its accuracy.
Leverage Prior Mappings
Reuse validated mapping logic from earlier TBM cycles, but review against the current version of the TBM Taxonomy to ensure alignment with the latest standards. Prior mappings should not be assumed correct without validation.
Stakeholder Validation
Engage IT Finance, FP&A, or Accounting partners to confirm ambiguous account classifications. Their institutional knowledge often provides essential context for accounts that appear vague or overlap multiple categories.
Tagging and Metadata Enrichment
Add optional enrichment fields (such as department, cost behavior, or CapEx/OpEx indicators) to strengthen accuracy and support downstream allocation rules. Metadata can also help prevent fallout reoccurrence by providing additional classification anchors.
Sustaining Data Quality
Ensuring high-quality Cost Pool data is not a one-time effort but an ongoing governance practice. Sustaining quality requires consistent validation, documentation, and ownership.
- Review cadence – Revalidate Cost Pool mappings quarterly or whenever accounts are added, repurposed, or retired.
- Version control – Maintain a changelog of mapping updates to preserve historical comparability and enable variance analysis across periods.
- Governance – Assign clear ownership for fallout resolution. For example, the TBM Administrator can validate mappings, while IT Finance provides sign-off to ensure accuracy.
Quick Tip: If your budget or GL includes account codes, you can leverage the mapping file created during the Chart of Accounts to Cost Pools process. If account codes are missing, keyword matching and metadata enrichment become essential for minimizing fallout and maintaining trust in reporting.
Fallout and Data Quality at the Resource Tower Layer
Once costs are categorized into Cost Pools and Sub-Pools, they are allocated into Resource Towers and Sub-Towers. This stage introduces greater complexity because costs are no longer grouped purely by financial classification but attributed to the distinct layers of IT infrastructure and delivery. Resource Towers (e.g., Compute, Storage, Network, End User, etc.) and their Sub-Towers provide the visibility needed to understand technology consumption and efficiency. Fallout at this layer typically reflects incomplete allocations, weak or missing drivers, or gaps in resource-level data. Because this is the bridge between finance and infrastructure operations, fallout here is particularly visible to both IT and Finance stakeholders.
Common Types of Fallout
Several recurring issues cause fallout at the Tower layer. These problems generally stem from gaps in allocation logic, misaligned drivers, or missing integrations with operational systems.
- Unallocated costs – Spend sitting in Cost Pools without flowing into any Tower or Sub-Tower.
- Overly generic allocations – Large “lump sum” allocations made without appropriate cost drivers (e.g., splitting software evenly across all Towers instead of using utilization).
- Driver mismatches – Missing or misapplied allocation drivers (e.g., allocating storage costs by headcount instead of GB consumed).
- Data integration gaps – Missing feeds from CMDB, HR, ITAM, or infrastructure monitoring systems, leaving Towers incomplete.
- Orphaned resource data – Servers, devices, or licenses tracked in a CMDB or ITAM system but not tied back to any financials, creating blind spots.
Risks of Ignoring Fallout at This Layer
Fallout in Tower allocations can have cascading effects. Because Towers form the foundation for mapping to Solutions and Consumers, inaccuracies here ripple throughout the TBM model.
- Tower cost distortion – Towers like Compute, Storage, or Network may appear cheaper or more expensive than reality, leading to misinformed optimization decisions.
- Decision blind spots – Leadership loses visibility into infrastructure efficiency, utilization, and cost drivers.
- Blocked Solution mapping – Fallout at the Tower layer cascades upward: incomplete Towers result in incomplete or misleading Solution allocations.
- Audit and compliance risks – Weak traceability between costs, drivers, and Towers undermines the defensibility of IT spend reporting.
Recommended Detection Practices
Catching fallout at this stage requires building structured QA and monitoring routines that highlight unallocated or poorly allocated spend. Detection practices should combine financial reconciliation with operational data validation.
- Tower reconciliation reports – Ensure total Tower allocations reconcile back to the input Cost Pool spend (allowing for minor rounding variances). A mismatch signals unmapped or orphaned costs.
- Driver completeness checks – Run QA to surface any Tower allocations missing driver references or using outdated metrics.
- Utilization vs. allocation checks – Compare actual utilization data (e.g., GB, CPU hours, tickets) against allocation outputs to confirm the logic is realistic.
- Trend analysis – Monitor Tower spend over time. Sudden anomalies or step changes often indicate fallout caused by missing data feeds or incorrect mappings.
Remediation Approaches
Addressing fallout at the Tower layer is about strengthening allocation design and ensuring complete system integrations. Organizations should approach remediation as a structured process rather than one-off fixes.
Strengthen Allocation Drivers
Replace arbitrary percentage splits with measurable, operationally valid drivers (e.g., ticket counts for Service Desk, VM CPU hours for Compute, network throughput for Network). Ensure drivers are both granular enough to reflect usage and sourced from authoritative systems.
Fill Integration Gaps
Work with IT Operations, Infrastructure, and Service Desk teams to ensure that systems of record (CMDB, monitoring tools, ITAM systems) are feeding the TBM model correctly. If certain feeds are not yet available, document assumptions and outline a roadmap for enrichment.
Validate Orphaned Resources
Cross-check CMDB, HR, or cloud accounts for resources that appear without financial linkage. Determine whether these represent shadow IT, misconfigured records, or legitimate costs not yet assigned. Each case should be logged and addressed through remediation or governance.
Stakeholder Alignment
Partner with Infrastructure owners and Finance to review ambiguous or disputed allocations. Finance stakeholders should validate the driver logic to ensure consistency with financial treatment, while Infrastructure teams confirm the operational accuracy.
Sustaining Data Quality
Long-term reliability of Tower allocations depends on governance and continuous improvement. Sustaining practices ensure fallout does not accumulate over time.
- Periodic recalibration – Reassess allocation drivers at least annually to confirm they remain valid and reflect current consumption patterns.
- Governance ownership – Assign accountability for Tower fallout jointly to Tower owners (responsible for data feeds and drivers) and TBM Admins (responsible for reconciliation and oversight).
- Version control and documentation – Record the drivers, data sources, and assumptions used for Tower allocations in mapping files or metadata fields. Maintain a changelog for transparency and auditability.
Quick Tip: Fallout at the Tower layer doesn’t always mean your data is “bad.” More often, it reflects a gap in driver design or missing integrations. Addressing fallout incrementally through a crawl-walk-run approach is expected in TBM practices—and doing so strengthens both the credibility and usability of your TBM model.
Fallout and Data Quality at the Solutions Layer
The Solutions layer is where costs tied to Resource Towers and Sub-Towers are attributed to the business-facing Technology Solutions defined in the TBM Taxonomy (e.g., Collaboration & Productivity, Business Applications, Data & Analytics). For organizations at higher maturity, costs may also be attributed to specific Offerings within a Solution, which enables detailed chargeback, showback, and total cost of ownership (TCO) reporting.
Fallout at this stage is particularly impactful because it is visible to business stakeholders. While fallout in Cost Pools or Towers might remain hidden in the financial back-end of the TBM model, fallout at the Solutions layer undermines the very outputs business leaders expect: transparency into what technology costs, who consumes it, and how it supports business value.
Common Types of Fallout
Fallout at the Solutions layer typically results from gaps in Solution definition, missing consumption linkages, or inconsistent practices across teams.
- Unassigned Tower/Sub-Tower costs – Spend that remains stranded in Towers without flowing into any Solution, creating incomplete Solution totals.
- Generic allocations without linkage to real consumption – Example: spreading all server costs evenly across Solutions, rather than using CMDB relationships or workload metrics.
- Solution catalog gaps – If the organization lacks a well-defined Solution or Service Catalog, TBM practitioners may struggle to establish consistent mappings.
- Inconsistent mappings across teams – Without a shared catalog and governance, different teams may assign the same infrastructure or application to different Solutions.
- Shadow IT and external services – SaaS subscriptions, cloud services, or departmental IT spend may bypass Solution attribution entirely, remaining invisible in reports.
Risks of Ignoring Fallout at This Layer
Because Solution-level outputs are consumed by executives and business partners, fallout here carries both financial and organizational risk.
- Business credibility loss – If significant portions of IT spend are unmapped, business leaders may dismiss TBM reports as incomplete or irrelevant.
- Skewed TCO reporting – Total cost of ownership for Solutions will appear understated, undermining comparisons across business capabilities.
- Missed optimization opportunities – Without full Solution costs, organizations may overlook redundant services or rationalization opportunities.
- Hindered chargeback/showback – Fallout disrupts the ability to attribute costs back to consuming business units, weakening accountability for consumption.
Recommended Detection Practices
To keep fallout visible and manageable, organizations should implement structured checks that highlight gaps in Solution attribution.
- Solution reconciliation reports – Validate that the total of Solution allocations reconciles back to the originating Tower spend, with only minor rounding variances allowed.
- Coverage reporting – Track the percentage of Tower spend assigned to Solutions; establish a benchmark and target for continuous improvement.
- Cross-team mapping reviews – Facilitate QA workshops with application owners, service managers, and Finance to uncover inconsistencies or duplicate mappings.
- Variance analysis – Compare Solution-level cost outputs to historical spend or business expectations. Large variances often highlight unmapped or misclassified costs.
Remediation Approaches
Remediation at the Solutions layer is both a technical and governance task. The goal is not only to close gaps but also to establish repeatable practices that prevent future fallout.
Establish or Refine the Solution Catalog
If a catalog exists, validate its alignment with TBM Taxonomy definitions and include Offerings where maturity allows. If no catalog exists, start with the baseline Solutions in the TBM Taxonomy and extend them as organizational needs evolve.
Leverage Resource-to-Solution Linkages
Where possible, use operational data from CMDB, ITAM, or application inventory systems to directly associate infrastructure and licenses with Solutions. This creates defensible mappings and reduces reliance on broad cost allocations.
Address Shadow IT
Engage Finance and Procurement teams to surface SaaS contracts or departmental IT purchases. Decide whether to bring these into the TBM model directly or document them as exclusions to maintain transparency.
Enforce Mapping Consistency
Create lookup tables or business rules that prescribe how Towers, Sub-Towers, or specific resources map into Solutions. Enforce these rules through governance and require that all new Solution entries follow a structured onboarding process.
Sustaining Data Quality
Sustaining accuracy in Solution-level reporting requires ongoing QA and continuous business engagement. Because this is the layer most visible to executives, governance discipline is critical.
- Ongoing QA checks – Automate reports that flag Tower spend left unallocated to Solutions or detect inconsistent mappings.
- Governance ownership – Assign accountability to Solution owners, with oversight from the TBM Office, to ensure fallout is remediated quickly.
- Version control – Document the mapping logic used (including rules, drivers, and assumptions) and maintain changelogs to preserve transparency.
- Business engagement – Hold regular review sessions with business stakeholders to validate Solution costs, reinforce credibility, and adapt the catalog as business needs change.
Quick Tip: Fallout at the Solutions layer is not just a technical issue—it is fundamentally a business alignment issue. Treat fallout remediation as a chance to engage stakeholders, refine your catalog, and strengthen organizational confidence in the TBM model.
Fallout and Data Quality at the Consumers Layer
The Consumers layer is the final step in the TBM model where Technology Solutions—and their associated costs—are attributed to the business entities that consume them. These entities are typically business units, departments, products, or projects, depending on how the organization defines accountability.
This layer is often where TBM becomes most visible to senior leadership, since outputs at this stage directly inform showback, chargeback, and unit cost reporting. Fallout at the Consumers layer has an outsized impact: even small gaps in consumer attribution can erode trust with business partners, distort unit costs, and weaken accountability for technology consumption.
Common Types of Fallout
Fallout at this layer usually emerges when costs are left unmapped or when business structures are incomplete or inconsistently applied.
- Unallocated Solution costs – Entire Solutions or portions of Solutions may not be mapped to any consumer, leaving gaps in accountability.
- Generic or placeholder consumers – Costs allocated to buckets like Miscellaneous, Shared, or Unassigned provide no meaningful business insight.
- Incomplete consumer hierarchies – Without a current corporate structure, product taxonomy, or project portfolio, consumer mapping may be inconsistent or impossible.
- Inconsistent treatment of shared services – Services such as email, networks, or security may be allocated differently by different teams, creating inequity across consumers.
- Lack of drivers or consumption metrics – Missing or poor-quality usage data (e.g., headcount, ticket counts, or device inventories) can prevent accurate consumer attribution.
Risks of Ignoring Fallout at This Layer
The consequences of fallout at the Consumers layer are severe because business leaders directly rely on these reports to understand IT value.
- Loss of business trust – If reports show large amounts of unallocated spend, business stakeholders may dismiss the entire TBM model as incomplete.
- Distorted unit costs – Unit cost calculations become unreliable if only part of a Solution’s costs are attributed to consumers.
- Weakened accountability – Without a clear consumer mapping, departments or product teams cannot be held responsible for the costs of the Solutions they consume.
- Budgeting and forecasting gaps – Fallout leaves Finance unable to reconcile IT cost drivers with business demand planning, reducing the value of TBM in budgeting cycles.
Recommended Detection Practices
To detect fallout at the Consumers layer, practitioners should monitor coverage, check for anomalies, and validate against business expectations.
- Consumer coverage reporting – Measure the percentage of total IT spend that is fully mapped to consumers, and establish thresholds for acceptable fallout.
- Variance analysis – Compare consumer allocations against headcount, license counts, or project funding levels. Mismatches often signal fallout.
- Exception reporting – Flag consumers whose allocations are disproportionately high or low compared to peer entities, prompting further review.
- Shared service checks – Review allocations for services such as networking or help desk to ensure they are consistently applied across consumers.
Remediation Approaches
Fixing fallout at the Consumers layer involves clarifying business structures, strengthening allocation drivers, and eliminating reliance on placeholder consumers.
Define or Refine Consumer Hierarchies
Align consumer definitions with official corporate structures, product portfolios, or project lists. Keep hierarchies current by updating TBM consumer structures after reorganizations, mergers, or new business launches.
Introduce Allocation Drivers
Select fair, transparent drivers (e.g., headcount, number of devices, tickets, or cloud consumption metrics) to allocate costs. Where data is missing, collaborate with system owners to capture required metrics or establish proxies.
Handle Shared Services Consistently
Develop and document rules for allocating shared services across all consumers. Policy-based methods (e.g., allocate network costs based on headcount, allocate help desk costs based on ticket volume) help ensure consistency.
Minimize “Miscellaneous” Buckets
Avoid relying on generic buckets wherever possible. If temporary use is unavoidable, document the rationale and actively plan for eventual migration of costs into valid consumer entities.
Engage with Business Stakeholders
Treat fallout not as a technical modeling flaw but as a business alignment challenge. Use fallout review sessions to engage Finance, business unit leaders, and IT in refining allocation methods and building shared accountability.
Sustaining Data Quality
Because fallout at this layer is highly visible, sustaining data quality requires robust governance and regular business engagement.
- Regular reconciliation – Ensure that consumer allocations always reconcile to the total cost of their parent Solutions.
- Driver validation – Reassess allocation drivers periodically to confirm that they remain valid and aligned with business realities.
- Governance oversight – Assign ownership for fallout at this layer to the TBM Office, in partnership with Finance and business unit CFOs.
- Audit trails – Maintain detailed documentation of allocation drivers, rules, and any manual overrides to preserve transparency and defensibility.
Quick Tip: Fallout at the Consumers layer is the most visible to business leaders. Treat every instance of unmapped or misallocated spend as a chance to engage stakeholders, validate fairness, and strengthen trust in the TBM model.
Techniques for Detecting Fallout
Addressing fallout begins with the ability to detect it consistently and systematically. Fallout can appear as unmapped costs, incomplete allocations, misapplied drivers, or integration gaps. Left unmonitored, fallout quietly erodes the credibility of TBM reporting. Detection requires both quantitative metrics and qualitative validation. The practices below outline not just what to measure, but how to operationalize those measures so that fallout is surfaced early, addressed promptly, and prevented from compounding over time.
Coverage Metrics
Coverage metrics measure what percentage of costs have successfully flowed through each layer of the TBM model (Cost Pools → Towers → Solutions → Consumers).
What to do:
- Calculate the coverage ratio at each stage: Coverage % = [Mapped Spend / Total Spend] × 100
- Track both percentages and absolute dollar amounts of unmapped spend. For example, “$3.2M (2.4%) of Tower costs remain unmapped to Solutions this month.”
- Trend results month-over-month or quarter-over-quarter to see if coverage is improving, stagnant, or declining.
Expected outcome:
Coverage metrics give you a quantifiable baseline for model completeness. Executives respond well to metrics framed as both percentages and dollars (e.g., “2% fallout equals $3.2M in unmapped spend”). Trending coverage over time highlights whether remediation efforts are working.
How this looks in practice:
In a commercial TBM platform (e.g., Apptio, Nicus), coverage metrics typically appear as QA or reconciliation dashboards. Dashboards often include red/yellow/green thresholds (e.g., <1% fallout = green, 1–3% = yellow, >3% = red).
Related processes: Coverage metrics should be part of monthly close and QA cycles and reviewed alongside reconciliation checks.
Fallout Buckets and Exception Reports
Unmapped or incomplete entries are often invisible unless explicitly surfaced. Routing fallout into visible buckets ensures it cannot be overlooked.
What to do:
- Route all unmapped entries into dedicated categories such as Unmapped – Cost Pool, Unmapped – Tower, or Miscellaneous.
- Build exception reports that flag:
- Missing assignments (e.g., Tower without a driver).
- Incomplete metadata (e.g., no owner or missing environment tags).
- Allocation logic that does not sum to 100%.
Expected outcome:
Fallout becomes visible, measurable, and actionable. Instead of silently disappearing from view, unmapped spend surfaces as explicit line items. Exception reports provide prioritized “to-do lists” for data stewards.
How this looks in practice:
Many TBM tools automatically route fallout to “Unassigned” categories. A best practice is to make these categories highly visible in reports—often placed at the top of hierarchies or highlighted in red.
Related processes: Exception reports should feed into monthly governance meetings so that fallout items are systematically addressed and closed out.
Reconciliation and Balancing Tests
Reconciling model totals at every handoff ensures that dollars are neither lost nor double-counted.
What to do:
- At each model stage, confirm: Total Input Spend (Layer N)=Total Output Spend (Layer N+1)±Variance
- Compare model totals with authoritative financial systems (GL, ERP, budgets). Small timing differences are acceptable, but unexplained variances should be flagged.
- Track fallout trends: a sudden increase may signal a new GL account, Tower, or consumer structure not yet mapped.
Expected outcome:
Reconciliation builds confidence in model integrity. Variance checks highlight issues before they distort business-facing reports.
How this looks in practice:
Most TBM platforms offer reconciliation dashboards that allow drill-down into discrepancies. For example, if Towers total $95M but Cost Pools show $100M, dashboards will highlight the $5M variance.
Related processes: Reconciliation should be embedded into financial close workflows, ideally automated where possible.
Benchmarking and Ratio Analysis
Contextualizing fallout with internal and external benchmarks helps you assess whether fallout levels are normal or problematic.
What to do:
- Compare fallout ratios across peer entities (e.g., business units, departments). Outliers often indicate localized issues.
- Use TBM Council benchmarks or industry survey data to determine whether fallout percentages are in expected ranges. For example: most mature organizations keep unmapped spend <1% at each layer.
Expected outcome:
Benchmarking identifies outliers and inequities. If one BU consistently carries higher fallout than others, remediation efforts can be targeted.
How this looks in practice:
Some TBM platforms include “benchmarking” dashboards or allow upload of reference data for comparisons. In other cases, this analysis is conducted offline in Excel or BI tools.
Related processes: Incorporate benchmarking into quarterly TBM reviews with executives, providing external validation of model quality.
Stakeholder Validation Sessions
Numbers alone cannot fully confirm accuracy—business validation is required to ensure mappings reflect reality.
What to do:
- Hold structured review sessions with Finance, IT service owners, and business stakeholders.
- Walk through specific accounts, Towers, or Solutions with subject matter experts to confirm whether allocations make sense.
- Document disagreements or adjustments as part of model governance.
Expected outcome:
Stakeholders gain confidence in the model because they see quality checks firsthand. Fallout is validated as either a real issue or a misinterpretation.
How this looks in practice:
TBM teams often use QA dashboards as the basis for stakeholder review, filtering on “Unmapped” or “Exception” entries. Notes from these sessions should feed directly into backlog items for resolution.
Related processes: Validation sessions should align with quarterly TBM steering committee meetings or budget cycles.
Automation and Monitoring
Manual checks are necessary but insufficient for ongoing assurance. Automation makes fallout detection proactive rather than reactive.
What to do:
- Configure dashboards to continuously monitor unmapped spend, exception counts, and reconciliation variances.
- Set up alerts or workflows that trigger when fallout exceeds thresholds (e.g., >3% of Tower spend unmapped).
- Store allocation rules and mapping logic in version control systems (e.g., Git, SharePoint, or TBM platform metadata) to tie fallout changes to model adjustments.
Expected outcome:
Fallout detection becomes continuous and proactive. Alerts prevent surprises during financial close, and version control accelerates root cause analysis when fallout increases after rule changes.
How this looks in practice:
In TBM platforms, automation often takes the form of QA dashboards with thresholds and notifications. For example, an email alert may be sent if unmapped spend exceeds $1M in a monthly cycle.
Related processes: Monitoring should be integrated into ITFM/TBM operational runbooks, alongside reconciliations and reporting deadlines.
Quick Tip: Treat fallout detection as part of monthly financial operations, not an ad hoc task. By combining metrics, reports, reconciliations, benchmarking, stakeholder reviews, and automation, you create a closed-loop process where fallout is continuously surfaced, measured, and addressed. The end result: a TBM model that is credible, transparent, and defensible at every layer.
Governance and Metadata Practices
Managing fallout effectively requires not only remediation at the data level but also consistent governance and metadata discipline. Without proper documentation and oversight, the same issues can resurface repeatedly, undermining trust in the TBM model. By embedding governance into fallout handling, you create traceability, accountability, and a repeatable process for continuous improvement.
Minimum Fields to Track for Fallout Resolution
At a minimum, every fallout remediation should capture metadata that makes it clear how and why a resolution was made. These fields allow your team (and auditors or new TBM practitioners) to understand the decision-making process:
Field | Purpose | Example Values |
mapping_method | Identifies how the mapping was assigned. | Manual, Keyword, Driver, Tag, System |
mapping_confidence | Communicates the reliability of the mapping. | High, Medium, Low |
data_source | Specifies the system of record for the data. | ERP, CMDB, Cloud Billing, HRIS |
last_reviewed_by + date | Records accountability for the most recent update. | Name + YYYY-MM-DD |
Practice: Add these fields to your mapping tables at every layer (Cost Pools, Towers, Solutions, Consumers). When fallout is identified and resolved, populate them consistently.
Outcome: Stakeholders can see not just what the resolution is, but how confident you are in it and where it came from — improving transparency and trust.
Change Management
Fallout resolution must be tied into broader financial and taxonomy processes. Ad hoc fixes without lifecycle discipline quickly erode model stability.
- Update mappings during fiscal planning cycles and Taxonomy updates. Treat fallout cleanup as a scheduled part of the financial calendar, not just as a reactive task.
- Maintain a changelog. Every change should include date, rationale, and approver. Whether you use Git, SharePoint, or a simple spreadsheet, this record is essential for auditability.
- Apply versioning. Keep old versions of mappings available for historical reporting or variance analysis.
Practice: Build fallout resolution into the same governance forums that oversee budgeting, forecasting, and taxonomy alignment.
Outcome: Mappings evolve in step with business changes, ensuring consistency across financial periods and avoiding surprises at reporting time.
For more information, visit our Organizational Change Management page to learn about techniques for managing change related to your TBM practice.
Stakeholder Engagement
Fallout is rarely just a technical issue; it reflects organizational processes and ownership. Bringing the right stakeholders into fallout resolution prevents TBM from being seen as an isolated Finance/IT activity.
- Regularly review fallout with Finance, Tower owners, and Solution owners. These groups often hold the context needed to correctly assign costs.
- Treat fallout resolution as shared accountability. Position it not as TBM “fixing” bad data, but as a collective responsibility to maintain accurate, trusted financials.
Practice: Schedule fallout reviews as part of quarterly business reviews or TBM governance council meetings.
Outcome: Fallout remediation becomes a collaborative process that improves both the TBM model and cross-team alignment.
Summary: Managing Fallout in Practice
Fallout is not a one-time error to be “fixed” and forgotten. It is a normal byproduct of operating a complex TBM model. The objective is not to achieve perfect elimination, but to build a model and operating rhythm where fallout is detected quickly, explained clearly, and remediated effectively.
By working through the preceding sections, you’ve seen that:
- Each TBM layer has unique fallout patterns (e.g., unmapped accounts in Cost Pools, orphaned assets in Towers, or unallocated spend in Consumers).
- Remediation steps are built into each layer’s process, whether that means refining mappings, tagging data, engaging subject matter experts, or adjusting allocation logic.
- Data quality practices and governance help reduce recurrence, ensuring fallout remains visible but manageable.
Key Principles for Ongoing Remediation
- Expect fallout, don’t fear it. Even highly mature TBM practices surface unmapped costs as new accounts, resources, or services enter the model.
- Use detection methods proactively. Coverage metrics, reconciliation tests, and anomaly reports are your early-warning system.
- Treat remediation as continuous improvement. Every fix improves not only the current model but also the organizational understanding of data sources, ownership, and financial accountability.
- Document and communicate. When fallout is identified and addressed, record the root cause, the resolution method, and who was involved. This creates organizational learning and prevents repeat issues.
By embedding these principles into your model operations, fallout becomes less a problem to eliminate and more a signal to improve data, processes, and alignment. Addressing fallout consistently strengthens the accuracy, credibility, and trust in your TBM practice — no matter what maturity level you are at today.
Next Steps
While you’re here, join the TBM Council to connect with peers and stay updated on all things TBM. Explore our Knowledge Base for frameworks, case studies, and how-to guidance. Learn more about the TBM Framework and how it supports smarter decision-making across IT and Finance, or find additional resources for building a TBM Model. You can also attend an upcoming event, pursue training or certification, or see how our partners are contributing to this area of TBM practice.
Join the TBM community: where innovators and leaders converge
The TBM Council is your gateway to a treasure trove of knowledge: think cutting-edge research papers, insightful case studies, and vibrant community forums where you can exchange ideas, tackle challenges, and celebrate successes with fellow practitioners.
We’re calling on organizations and forward-thinking individuals to dive into the TBM community. Participate in our events, engage in our discussions, and tap into a vast reservoir of knowledge. This isn’t just about networking; it’s about contributing to and benefiting from the collective wisdom in navigating the dynamic world of cloud computing.
