the afp a maturity model

The AFP FP&A Maturity Model

FP&A is evolving from an offshoot of the accounting organization into a forward-looking and strategic function; it performs not only the core activities of budgeting, forecasting and planning but also relies on increased use of data and analytics, an expanded skillset and advanced processes to partner with the business and drive better decisions to improve enterprise performance. Different FP&A teams are at different phases in this evolutionary curve. Some are just beginning their journey. Others have reached a higher level of maturity.

The FP&A maturity model developed by AFP in collaboration with members of its FP&A Advisory Council is designed to help companies identify where they are on that maturity scale along four critical domains:

1. Organization/People/Skills

2. Business Process

3. Technology

4. Data

In each of these domains, the model identifies five core elements. And for each element it includes three statements of maturity: elemental, emergent and optimized. Using a companion, detailed self-assessment tool, FP&A teams can rank themselves on a scale of 1-10 to identify where they’re performing well and where they may need to improve.

Next, the model includes five key steps FP&A teams can take to improve their performance in each of the four domains. There’s also a companion addendum that provides more detailed “how-to” steps for companies that want further advice on how to evolve from their current state to an optimized state.

“The model is a valuable tool to help FP&A organizations assess where they are and where there are opportunities to grow and improve,” said Gaileon Thompson, Senior VP, Global Consumer Operations & Technology Finance at Citibank, and the Chairwoman of AFP’s FP&A Advisory Council. “And for those teams that are further along the maturity spectrum, the tool also serves as a validation for just how far they’ve come.”

AFP wants to thank the following Advisory Council members for their invaluable contributions:

Jon Kanter CFO, Goodwin Procter LLP

Mitch Max Partner, BetterVu

Philip Peck VP Finance Transformation, Peloton

Tom Russell VP, Financial Planning & Analysis, Welltower

Gaileon Thompson Senior Vice President, Global Consumer Operations & Technology Finance, Citibank

Tijana Balotic-Truong Finance professional

INTRODUCING: THE AFP FP&A MATURITY MODEL

THE AFP FP&A MATURITY MODEL 3

> Management reporting> Plan/Forecast performance> Resource allocation> Performance measurement> Analytics

> Business Partnering > Skills and Capabilities> Business Knowledge> Ownership and accountability> Business Culture

> Modeling and Planning > Reporting and Analysis> Toolkit Alignment to Business Planning > Data Management and Integration> Dashboards and Advanced Analytics

> Data quality> Data access> Data usage> Data integration& management > Data governance

Business Process

Organization People Skills

Technology

Data

THE META MODEL


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BUSINESS PROCESS PEOPLE AND SKILLS TECHNOLOGY DATA

MATURITY MODEL OVERVIEW

Relatively error free process looks forward but with limited business collaboration with access to one data source pulling from disparate systems.

Standardized business platform with some robust purpose-built applications, reliant on multiple data management tools with some degree of manual effort with moderate ability to deliver dashboards and analytics.

Improved data quality where governance exists with reasonably good access to primarily financial data, but data management and governance are not deployed consistently across the organization.

The organization is unclear as to how to look forward, and FP&A has only moderate resources to engage with the business with some ability to perform diagnostics and understanding of the business, resulting in diffused accountability.

Forward looking, error free processes are planned jointly with operations with access to a single source of data.

A fully integrated and robust modeling and purpose-built planning platform seamlessly integrated with self-service analytics and visualization capabilities and reliant on a central repository.

Comprehensive and fully integrated enterprise data model with timely access to centrally managed operational and financial data that is part of a comprehensive and formalized governance structure.

The organization is forward looking, and FP&A is viewed as a trusted business adviser that delivers advanced analysis and ensures business leaders are accountable for delivering results. FP&A receives professional training like AFP’s Certification program to develop the necessary skillset.

Annual plans prone to error with little transparency viewed with skepticism by the business and reliant on manual input from multiple sources.

Planning and ad-hoc reporting are done primarily in Excel and are heavily reliant on manual effort with a limited ability to deliver dashboards and advanced analytics.

Lower quality with manual access to only financial and internal data that’s managed on a decentralized basis with limited formalized governance.

The organization focuses on past performance and finance is mainly performing traditional planning activities and has only a basic understanding of the business and primary ownership of the financial plan and forecast.


Management Reporting

Plan/Forecast Development

Resource Allocation

Performance Measurement

Analytics

The process is mostly error free and produces forward-looking, actionable information; FP&A creates a rolling 18-24 months forecast tied to business metrics and the plan is used frequently in business discussions.

FP&A tracks accuracy to help improve forecasts used to support timely business decision-making; forecasts and plans are developed beyond the fiscal year on an enterprise basis sharing common assumptions for business metrics.

Resource usage is planned jointly with the business and the financial and operational planning cycles are in sync; plans to measure and consume shared resources are collaboratively prepared, using complex allocation methods, e.g., take-or-pay, variable with cap, etc.

Errors are rare and users trust the information; FP&A benchmarks ops and financial KPIs against the competition. Each BU develops its own measures within a corporate framework aligned with overall strategy.

FP&A has access to a single source of the truth, and understand how to interpret the information to come up with forward-looking action items. FP&A and the business share common tools leading to timely business decisions, based on financial and non-financial measures.

BUSINESS PROCESS ASSESSMENT TOOL

Your Score Your Score Your Score Your Score Your Score

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The process exhibits persistent errors and is primarily backward looking; forecasts are updated monthly and prepared centrally, with minimal input from the business and is only occasionally referenced in business discussions.

Plans are developed annually, with a focus is on 12-month fiscal budget commitments that are not always tied to drivers Plans are used primarily to report variances against budget, often tied to compensation.

FP&A allocates resources based on ability of service provider to deliver; costs for service are allocated with little transparency as to causation and resources are planned and locked in for the duration of a fiscal year.

Persistent errors lead users to view results with skepticism; measures are retrospective, established on a corporate level and provide limited insight into performance drivers and derived directly from financial statements.

Data, manually sourced from multiple sources, may not tie back to other official performance reports; historical analysis is shared via static documents using simplistic tools with a focus on either financial, or operational performance, without comparison to external benchmarks.

Reports may contain some errors and FP&A still relies on primarily financial information with some key operational metrics; finance is still the primary creator of the forecast with some business input.

FP&A includes forecasts, which extend within the current fiscal year; FP&A negotiates budget commitments with business units, sharing information only as needed.

Resources may be fully allocated, but there is limited ability for business users to appreciate, understand and influence the cost; FP&A shows some responsiveness to fluctuating business needs during the year.

Errors are infrequent and users have ‘trust but verify’ view of measures, which include comparisons or more detailed view of performance. KPI’s are developed within the BUS but are disconnected from corporate metrics.

Data quality is high when pulled from single source, but errors occur once multiple source systems are introduced. Analysis enables some business decisioning, but lacks granularity because it includes only recent performance and short-term forecast.


Business Partnering Skills and Capabilities Business Knowledge Ownership and Accountability

Organizational Culture

PEOPLE AND SKILLS ASSESSMENT TOOL

FP&A is regarded by the business as a trusted strategic advisor, spending the balance of its time providing value added insights and helping to drive improved business performance and decision making.

FP&A has predictive and advanced abilities to understand business relationships, perform statistical modelling, and deliver business insights; the function has shifted from “what and why” towards “what’s next and how do we make it happen,” Staff receives professional development like AFP’s FP&A certification program.

FP&A exhibits a comprehensive understanding of operational and financial business drivers, and has deep knowledge and expertise across all facets of the business; it’s recognized as business Subject Matter Expert.

The organization shares ownership for the business and financial plan; ultimately, business leaders are accountable for delivering results.

The organization is forward looking and embraces both strategic and operational change, and is willing to take calculated risks and tolerate failure on the basis that it will lead to future success.

FP&A engaged with the business providing requested information to decision makers, and with a moderate amount of time available for analysis, problem solving and insight development.

FP&A has some ability to perform diagnostic analysis around key business and financial drivers; it has some focus around root cause analysis and “why it happened,” with a greater reliance on enabling technology to perform data integration, data consolidation, and reporting.

FP&A possess more robust understanding of underlying business drivers, business value chain, and unique business complexities, and thus has greater ability to perform meaningful analysis.

There’s a diffused ownership and accountability for various elements of the financial plan and forecast.

The organization appreciates the need to look forward as well as back, but is unclear in how to do that; it does not fully accept finance as a strategic function that plays a key role in charting the course of the company.

FP&A team seen as a back-office, reactive provider of information, with most of its time spent on data collection, transformation, reconciliation, validation, and reporting with limited bandwidth for more value added-activities.

FP&A knows how to perform descriptive analytics, and run basic planning and forecasting activities, process coordination, data consolidation and reporting; its primary focus around historical performance, with a focus on “running the process” instead of driving insights.

FP&A has only a basic understanding of the business, including key business drivers, end-to-end business value chain, core capabilities, and unique aspects of the business.

Primary ownership of the financial plan and forecasts lives in Finance; the businesses and functional areas have limited ownership and accountability.

The organization is more focused on understanding what’s happened in the past, and isn’t committed to a culture of change to prepare it for the future, or views finance as a leading voice for change.


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Modeling and Planning

Reporting and Analytics

Toolset Alignment to Business Planning

Data Management and Integration

Dashboards and Advanced Analytics

FP&A leverages a fully integrated enterprise modeling and planning platform, with centralized administration, common driver values and business rules; it has capabilities for driver-based modeling, what-if analysis, simulation, and scenario planning.

FP&A leverages standardized planning platforms; data integration requires some manual effort; FP&A has moderate level of capability for driver-based modeling, what-if analysis, simulation, and scenario planning.

FP&A uses a standardized, enterprise reporting platform that’s seamlessly integrated with a common data repository; there’s a strong level of automated self-service reporting and analysis capabilities.

FP&A relies on standardized and ad hoc reporting, supported through enterprise tools and Excel.

FP&A uses robust purpose-built applications that have been implemented and deployed across the organization for core planning and reporting processes and for all of related operational and business planning processes (e.g., Strategic Planning, Capital Planning, Workforce Planning, project Planning).

FP&A uses robust purpose-built applications that have been implemented and deployed across the organization for core planning and reporting processes and for some but not all of the related operational and business planning processes.

All data for core FP&A processes is available and accessed via a centralized data repository; information architecture automates the sourcing, transformation, integration, and distribution of data to analytic applications; master data is managed through a single enterprise application.

Data management and integration is supported by a combination of enterprise applications, Excel models, and shadow systems; there are emerging pockets of capabilities for automation and streamlining but there’s a lack comprehensive of architecture or vision.

FP&A relies on robust analytical environment where dashboards are tailored to various types of end users, provide common analytical drill paths, and visualize information in unique and insightful ways.

FP&A has some ability to define and deliver dashboards, and advanced analytical capabilities; financial analysts are beginning to use more advanced modeling techniques, tools, and rely on existing Excel

TECHNOLOGY ASSESSMENT TOOL


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Planning and forecasting models primarily reside in Excel and with limited systematic integration upstream source systems and consolidating applications; there’s a limited capability for driver-based modeling, what-if analysis, simulation, and scenario planning.

There’s still some degree of manual effort involved in data collection, transformation, reconciliation, formatting, and reporting, and just some self-service capabilities.

The existing applications supporting the core planning and reporting processes and related business planning processes do not provide the capabilities, functionality, and usability required by the operational processes.

Data sourcing, transformation, integration, aggregation, and promulgation heavily dependent on manual processes, Excel models, and various off-line disconnected shadow systems; master data is primarily managed through manually intensive processes and off-line tools.

There’s a limited ability to define and deliver dashboards, data visualization, and advanced analytical capabilities. FP&A is heavily reliant on Excel, and challenged by access and availability of data.


Data Quality Data Access Data Usage Master Data Management

Data Governance

Finance has a comprehensive and fully integrated enterprise data governance model; it uses robust tools and processes for managing the lineage and flow of data from source systems to staging / repositories to planning and reporting analytical applications.

There’s improved data quality where standard data governance exists, and data management and integration are supported by some degree of enabling technology and process controls; however, finance faces isolated pockets of data quality issues resulting from shadow systems, manual processes, etc.

FP&A faces lower level of data quality where potentially significant known issues persist; there’s a high degree of manual effort required for data sourcing, transformation, collection, and consolidation.

FP&A has complete and timely access to the right information from a trusted source with a high level of data quality and surety.

FP&A has reasonably good access to required data supporting the planning, forecasting, and reporting processes; it has strong ability to source data from a qualified source with limited integration activity and manual effort.

FP&A must use a manual effort to access and collect the data it needs for planning and reporting purposes, and the data may reside in multiple, disparate source systems, offline models, and often requires downstream data transformation.

Data sources incorporate a full array of financial, operational, customer, competitive benchmark, etc., from internal and external sources. FP&A uses big data principles to support advanced analytics.

FP&A uses primarily financial data with moderate integration and usage of operational information from internal sources It makes limited and isolated usage of external information and big data sets.

FP&A uses only internal and financial data for planning and reporting.

Master data is managed centrally and promulgated consistently throughout all analytic applications and reports; FP&A relies on enterprise tools and technology which provide automation and support streamlined processes.

There are pockets of centralized management supported with enabling tools and technology but not consistently deployed throughout the organization; master data management still requires manual effort, and off-line models.

Master data is managed in a decentralized, non-standard manner by multiple people; there’s significant manual effort with limited to no enabling technology.

The organization has a comprehensive formalized governance program, processes, and procedures around managing the collection, identification, storage, and usage of data across the enterprise.

The organization has some elements of a formalized governance program, processes, and procedures around managing the collection, identification, storage, and usage of data across the enterprise.

There is limited formalized governance, processes, and procedures around managing the collection, identification, storage, and usage of data across the enterprise.

DATA ASSESSMENT TOOL


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Business Process

Management Reporting Develop a plan to track and measure error rate and extend focus into future years, while engaging other stakeholders and incorporating non-financial metrics to strategic measures.

Plan/Forecast Development Extend forecast horizon and increase time spent on forecasting, while improving accuracy; engage the business to link the forecast to operational drivers translating into predictive measures of financial performance.

Resource Allocation Assess shared resource allocation and plan collaboratively using meaningful, driver-based measures, fostering a partnering culture around shared services and regular communication around plans for meeting user needs.

Performance Measurement Measure and track error rates and incorporate external and internal benchmarks into reporting, using strategic, financial and non-financial KPIs across the organization.

Analytics Identify “gold sources” of financial and operational data, while ensuring analytics has appropriate human skills and technology; engage business partners to add value with an emphasis on action items, shifting to driver-based modeling and predictive analytics.

People & SkillsBusiness Partnering Meet regularly, consider shadowing or embedding FP&A staff in the business to offer analytics solutions to business problems; ensure everybody knows FP&A has a seat at the decision-making table.

Skills and Capabilities Attend events and learn from peers about best of breed, as well as additional informal and formal training.

Business KnowledgeEncourage each FP&A team member to spend time working on the “front lines” of the business; invest in industry-specific events and education and learn by listening to business partners.

Ownership/AccountabilitySet up business reviews but clearly communicate expectations on ownership of conclusions, and ensure BU leaders sign off on budgets, while building key metrics—tied to compensation—into business leaders’ goals.

Organizational CultureBuild a 3-year plan tied to corporate strategy and expose senior leaders to best practices; identify “change champions” within the business who can influence decision makers and consider “stealth innovation” to show what’s achievable.

HOW TO MOVE UP THE MATURITY CURVE: FIVE KEY STEPS


DataData QualityDevelop a comprehensive list of data quality issues including data elements, data source, core issues(s), and known remediation methods and identify initiatives, establish a roadmap, and scope out the first project for fixing the data quality issues.

Data AccessUnderstand and document the current state environment supporting data access and data availability including data elements, data sources, timeliness, completeness, and usability; make sure data is useable and you can access it in a timely manner.

Data UsageClearly define the use cases associated with making additional data elements and sources available for planning, reporting, and analysis purposes. While it’s good to leverage existing data, it’s important to identify what other data (external, big data and non-financial data) needs to be tapped.

Data Integration and ManagementIdentify and catalog all of the necessary data components and activities associated with data integration and data management in the existing environment; take inventory of all hierarchies, data movement, data transformation, data mapping, data loading at a fairly granular level.

Data GovernanceDefine and document the key data governance needs across the organization, including the relationship requirements among different components such as data, business process, how you will use the data and ownership; for example who has the authority to add a new account and how?

TechnologyModeling and PlanningUnderstand and document the current state environment supporting modeling and planning, such as activities and process steps, roles and responsibilities, data sources, models, calculation logic and algorithms, usage of tools, duration, quality and timeliness of output.

Reporting and AnalysisDefine the key organizational reporting and analysis needs across multiple perspectives (financial, external, management, operational, transactional); include not just financial but also external and operational reporting and metrics, as well as transactional, real time information.

Toolkit Alignment to Business PlanningDevelop clear set of initiatives and roadmap for implementing more advanced business-process-specific functionality and capabilities. Figure out what are the independencies between initiatives and which need to be pursued first and determine the appropriate modeling and planning technology platform.

Data Management and IntegrationDefine and document the key data management and data integration needs across the organization. Touch on things like how to source the data, whether the data needs to be transformed and how it must be stored, aggregated and how to define different hierarchies.

Dashboards and Advanced AnalyticsDetermine the dashboard, visualization, and advanced analytics technology platform; step back to consider what tool (or limited set of tools) are required in order for the organization to communicate more easily.

HOW TO MOVE UP THE MATURITY CURVE: FIVE KEY STEPS

About the Association for Financial ProfessionalsThe Association for Financial Professionals (AFP) is the professional society committed to advancing the success of its members and their organizations. AFP established and administers the Certified Treasury Professional and Certified Corporate FP&A Professional credentials, which set standards of excellence in finance. AFP hosts the AFP Annual Conference, the largest networking event worldwide for over 6,500 corporate finance professionals.

General Inquiries [email protected]

Website www.AFPonline.org

Phone +1.301.907.2862

AFP, Association for Financial Professionals, the AFP logo, CTP, Certified Treasury Professional, the CTP logo, FP&A, Certified Corporate Financial Planning & Analysis Professional and the FP&A logo are registered trademarks of the Association for Financial Professionals. ©7/17 Association for Financial Professionals, Inc. All Rights Reserved. FPA-17_Maturity_Model 07/19/2017

the afp a maturity model

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