Modernizing FP&A with Tech

Dec 5, 2025

Modernizing FP&A with Tech

Financial planning and analysis (FP&A) has been under pressure to deliver faster insights, deeper forecasting accuracy and better strategic collaboration. Many finance teams still depend on spreadsheets – surveys show that 96% of FP&A professionals rely on Excel for planning and 93% use spreadsheets for reporting, often in parallel with a planning system[1].

This study looks at why leading finance teams are modernizing their FP&A toolkits, the limitations of traditional tools like Excel, and the patterns emerging from finance leaders who have refreshed their FP&A processes.

It also explores why some CFOs adopt modern technology stacks while others plateau, and suggests why a modern AI‑enabled platform such as Pluvo could be a solution worth discussing.

Voices from the field

Over the past few months we’ve spoken with CFOs and FP&A leaders at mid‑market firms and large enterprises to understand their lived experience. Several candidly told us that they “spend more time wrangling spreadsheets than working with the business” and that this dependency on Excel has become a source of frustration.

One finance vice‑president at a technology company described how their team built elaborate forecasting models in Excel that only a few people truly understood — whenever a key person was out sick, the whole process slowed to a crawl.

A CFO at a manufacturing firm summed up the sentiment by saying they were “done being data janitors”; they want tools that automate consolidation so their team can focus on value‑added analysis. These conversations informed the themes and recommendations that follow.

Why Modernize?

Problems with Manual and Spreadsheet‑Driven FP&A

Heavy manual workload and time spent on data preparation. EY’s 2025 FP&A Trends research found that although companies have adopted technology, manual work is still a restriction for 81 % of finance teams[2]. In many organizations, only 35 % of FP&A time is spent on high‑value activities such as generating insights; the rest goes to data collection and validation[3].
Excel is ubiquitous but lacks scalability and control. Surveys show that 52 % of FP&A departments use Excel as their primary planning application[4]. Workday notes that Excel is familiar and flexible but becomes a barrier when planning needs to be collaborative and dynamic; issues include version control problems, siloed data, limited scalability, and audit risks[5]. FP&A Trends’ poll acknowledges Excel’s dominance but highlights its limitations in governance, scalability and data integration[6].
Difficulty forecasting beyond a few months. Over 63 % of finance teams cannot forecast beyond six months[6]. Traditional Excel models are linear and assumption‑heavy, making it hard to update assumptions quickly when business conditions change[7].
Slow scenario planning and lack of real‑time insights. Only 22 % of companies can run scenario analyses within a day, and 21 % cannot run them at all[8]. Manual spreadsheets are poorly suited to dynamic scenario planning and collaboration across departments.
Integration and data quality problems. The SMB Financial Planning Technology report notes that 61 % of SMBs still rely on manual Excel uploads despite integrating some systems[9], and poor data quality blocks 49 % of CFOs from making critical decisions[10].

Patterns from Finance Leaders Who Have Refreshed Their FP&A

Move Away from Stand‑Alone Spreadsheets

Microsoft’s “Modern Finance” transformation. Microsoft’s finance function struggled with fragmented data sources and manual workflows. By introducing AI across forecasting, variance analysis and predictive analytics, they reduced manual work and accelerated the “insight‑to‑action” cycle. CFO Takeshi Murakami highlighted that shifting from manual, fragmented processes to an AI‑driven model required a mindset change and a single source of truth[11].
Vodafone’s forecasting overhaul. Vodafone relied heavily on Excel and lacked predictive analytics. The finance team rebuilt forecasting using machine‑learning models and transparent scenario planning; they achieved faster, more accurate forecasts, real‑time scenario planning and reduced manual reporting[12]. Finance leader Gizelda Ekonomi said AI doesn’t replace human insight but multiplies it; a clear strategy and strong leadership were critical[13].
Caterpillar and unified data for rolling forecasts. Caterpillar partnered with EY to build a central AI‑enabled forecasting platform that unifies data, enabling continuous rolling forecasts. Dennis Sparacino noted that the technology not only sped up forecasting but changed how the team thinks—moving from building reports to modelling scenarios and making decisions faster[14].

Integrated Planning and Business Partnering

Walmart’s product‑management approach. In FP&A Trends’ survey debrief, Walmart’s Director of Product Management described how treating FP&A tools as products improved data quality and engagement. They track success by outcomes—such as reducing Excel use by 80 %—and use a “Four‑in‑a‑Box” methodology that involves customers, product managers, developers and UX specialists[15][16]. This model encourages collaboration and reduces non‑value‑adding activities.
SAP’s focus on data‑driven decision‑making. Nick Verhoeven from SAP emphasised that the real challenge is data quality and collaboration between finance and technology teams. Only 10 % of organizations involve IT in managing data duties; bridging this gap through “fusion teams” allows finance and technology to co‑own data objects and improve decision‑making[17].
Continuous planning and cross‑functional collaboration. Workday’s 2025 trends report notes that integrated, cloud‑based planning platforms are essential. CFOs must align with CIOs, enable real‑time data sharing, and invest in upskilling to make the most of AI[18]. Limelight research shows that 70 % of teams now use cloud‑based FP&A platforms, with cost reductions around 15 %[19]. Triple Crown Sports, for instance, reduced report preparation time by 98 % and improved collaboration by adopting a cloud‑based FP&A tool[20].

Upskilling and Mindset Shifts

Need for AI and data skills. Workday reports that 99 % of finance leaders see benefits in adopting AI but 75 % believe their organisations lack the skills to fully leverage it[21]. Bain & Company highlights that at Microsoft, AI agents now automate tasks previously done in Excel, but autonomy requires finance professionals to redesign processes and re‑evaluate decision rights[22].
Reducing redundancy and embracing AI. Vena’s CFO Melissa Howatson notes that introducing the right technology makes processes repeatable and defined[23]. Craig Schiff (BPM Partners) adds that 57 % of firms are using AI in finance, primarily for data analytics and predictive modeling[24]. These leaders emphasise that AI augments human decision‑making and frees time for strategic activities.

Outcomes Achieved

Higher forecasting accuracy and agility. Case studies show that AI‑enabled platforms deliver unbiased forecasts, faster scenario planning and reduced manual labour. Vodafone and Caterpillar reduced reporting time and improved accuracy[12][14].
Greater collaboration and data transparency. Integrated platforms enable finance to partner with sales, operations and technology. Live data orchestration is critical; Josh Baker from PJT Partners (an investment bank) stressed that integrating live data is essential to enable AI and advanced forecasting[25].
Strategic role for finance. With manual tasks automated, FP&A teams can focus on driver‑based planning, risk analysis and advising business units. Case studies highlight culture changes: finance teams shift from report builders to strategic partners[14].

Why Some CFOs Scale Tech Stacks While Others Plateau

The question of why some finance leaders aggressively modernize while others remain tethered to spreadsheets boils down to organisational mindset, perceived risk and the pain of staying the same versus the pain of change. Several patterns emerged:

Factor	Leaders Who Scale	Leaders Who Plateau
Vision & Strategy	View FP&A as strategic lever; invest in technology aligned to business goals and ROI. Use data as a product and adopt AI to enhance human judgment (e.g., Microsoft, Vodafone, Caterpillar)[11][12].	See FP&A as back‑office function. Focus on reporting rather than analysis. Lack long‑term technology vision; often respond only to urgent problems.
Leadership Mindset	CFOs champion change, build cross‑department “fusion teams” and encourage experimentation. They actively reduce spreadsheet reliance and measure success through outcomes (e.g., reducing Excel use by 80 %)[15].	CFOs may become “plateaued” – comfortable in existing tools and routines. A LinkedIn post warns that a plateaued CFO stops challenging and adapting, holding the business back[26].
Skills & Capacity	Invest in upskilling and hire finance professionals with data science and analytics expertise. They recognise that AI adoption requires new skills[21].	Lack skills or training to leverage modern tools. Many organisations cite lack of data skills and cost as barriers to AI adoption[27][10].
Implementation & Integration Approach	Choose cloud‑based, modular platforms with quick time‑to‑value and pre‑built integrations. Focus on reducing manual tasks rather than replacing Excel entirely; provide Excel export for ad‑hoc analysis[28].	Adopted tools may be complex to implement or poorly integrated; they continue using Excel because integrations are painful or processes are not re‑designed. 61 % of SMBs still rely on manual Excel uploads even after integrating systems[9].
Change Management	Engage business partners early, align finance and technology, and communicate benefits. Limelight and Workday advise starting with high‑impact use cases and demonstrating quick wins[29][19].	Resist change due to familiarity with Excel and fear of disruption. SMB surveys show 50 % of non‑adopters say manual methods work fine and cite cost, complexity and lack of time[30]. Leaders may postpone investment until pain is acute.

Why Excel Is No Longer Sustainable

Persistent reliance but growing pains. Despite decades of “Excel killers,” spreadsheets remain widely used because of their flexibility and zero marginal cost. However, the risks are well documented: version‑control issues, lack of transparency, collaboration bottlenecks, limited scalability and compliance risks[31][1]. More than half of organisations cannot run scenarios quickly or predict beyond six months[8][6].
Integration demands exceed spreadsheet capabilities. Modern FP&A requires data integration from ERP, CRM, HR and external sources. Spreadsheets struggle to consolidate high‑volume, real‑time data and cannot provide audit trails or collaborative workflow[5]. Excel becomes the integration layer when systems are disconnected, but this leads to errors and inefficiency[28].
Manual work drains capacity. Finance professionals spend 39 % of their time on manual, automatable tasks[10]. This time could be redirected to analysis and strategic planning if processes were automated.

Opportunities and Recommendations

Modern finance leaders are moving towards connected, AI‑enabled planning platforms that augment human judgment and automate the mundane. Pluvo is an example of a next‑generation FP&A platform that aligns with these trends. The platform integrates with accounting software, uses AI to analyse data, builds models, and allows users to branch scenarios and automate reports[32]. Testimonials from CFOs and finance managers report that Pluvo bridges strategic goals with financial models and reduces error‑prone tasks[32].

For leaders considering an FP&A refresh, consider these actions:

Assess current pain points – quantify manual hours spent on data preparation and forecast accuracy gaps. Surveys show that reducing manual tasks from 39 % to under 20 % is a compelling outcome[33].
Build a technology roadmap – start with high‑impact use cases such as driver‑based planning, rolling forecasts or scenario analysis[29]. Choose modular, cloud‑based tools that integrate easily and deliver quick wins[34].
Invest in data and skills – ensure data quality through governance and involve IT early; build cross‑functional “fusion teams” to co‑own data[17]. Upskill finance teams in analytics and AI[21].
Encourage cultural change – lead by example; challenge the status quo and recognise that staying comfortable with legacy tools may plateau the business[26]. Communicate the value of modern tools not as “AI features” but as capacity‑creating solutions[33].

Closing Note

Finance leaders who embrace integrated, AI‑driven FP&A platforms demonstrate faster forecasting, improved accuracy and stronger strategic partnership with the business. Those who continue to rely on spreadsheets face increasing risk, slower decision cycles and difficulty scaling. If you’d like to explore how modern platforms like Pluvo can help your team move beyond spreadsheets and unlock capacity for strategic work, We’d be happy to discuss further or arrange a call.

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[1] [9] [10] [28] [30] [33] [34] SMB Financial Planning Technology Adoption Report 2025 | Compass AI