Budgeting, Planning and Forecasting Budgeting, Planning and Forecasting

Introduction Enterprise Finance AI Financial Budgeting & Forecasting FP&A-Led Integrated Business Planning Case Studies Conclusion Request a Demo

Gaining Agility in Strategic, Financial & Operational Planning

Budgeting, Planning and Forecasting

Introduction

For enterprise Finance leaders, AI is at the forefront of interest. Purpose-built solutions such as OneStream’s Sensible ML (Figure 3) expands FP&A-led business planning efforts with out-of-the-box, purpose-built ML forecasting. With such solutions, Finance teams can quickly create forecasts and share insights never thought possible with other business teams. AI-powered operation planning provides significant benefits:

Aligning Business Plans

Managing through the uncertainty of today’s business environment requires organizations to eliminate decision silos and unify operational plans with financial goals. Accordingly, modern FP&A teams are no longer compromising. Instead, they’re now leading efforts to bring together sales plans, demand forecasts and financial plans. Those efforts deliver rolling forecasts, scenario plans, reporting and insights at every level of the organization – all while doing it at scale and leading the conversation to drive business impact. At OneStream, we take Finance further by uniquely unifying AI at the core of the OneStream platform to power financial and operational insights and forecasts while increasing productivity for every employee.

As modern Finance teams at large companies gear up to conquer challenges and seize opportunities, the stakes have never been higher. The current landscape is shaped by the shifting sands of rising interest rates, disruptions in the supply chain and the relentless march of technology. As a result, the call to take Finance further resonates louder than ever. So how can modern Finance organizations answer that call? Forward-thinking FP&A professionals must harness the power of trusted, governed financial forecasting software. By design, these budgeting and forecasting software solutions vastly increase forecasting agility, improve accuracy and deliver massive productivity across decision-making processes in sophisticated organizations. Such organizations don’t just set financial targets or budgets. Instead, those organizations take Finance further by continually monitoring performance and developing processes to dynamically update the operational assumptions required for Integrated Business Planning (IBP).

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Those organizations are in stark contrast to Finance teams who still rely on silos of spreadsheets or old enterprise performance (EPM) applications to manage their budgeting, planning, forecasting and analysis processes. Those teams spend more time on low-value tasks rather than collaborating with – and providing insights to – business partners for key decision-making.

Forward-thinking FP&A teams think differently. How? They focus on creating the scale to see holistically across the organization. But they also understand the need for flexibility to drill down to product, customer and other operational details. These FP&A teams don’t compromise, either. In other words, they don’t settle for inflexible tools that hold back the teams’ progress, and AI is enabling this progress (Figure 2).

Enhanced speed and accuracy: AI-powered operational planning automates many manual tasks involved in traditional planning, ultimately reducing the time to generate and share the results. In addition, companies operating in today’s digital economy have access to more data than ever. AI can process this ever-growing data and consider additional business intuition – such as events, pricing, competitive information and weather – to produce more accurate predictions. Plus, AI-enabled planning can also automate many of the repetitive, menial tasks required in operational planning. The time saved gives analysts more time to develop strategic recommendations for the organization based on the results of AI-generated plans and scenarios. Improved risk management: Finance can identify and react to potential risks easier and quicker, and more easily capitalize on opportunities by leveraging AI-powered operational planning. For instance, AI can incorporate substantially more drivers, both internal and external, to automatically identify correlations, patterns and anomalies across thousands of products and locations. Those insights can then be used to make better-informed decisions on managing risk and preparing for potential scenarios. In turn, this efficiency will dramatically cut down the amount of time needed to complete various “what-if" analyses to better plan for the rapidly changing environment. Planners can therefore now focus more on leveraging the potential scenarios rather than producing them. Better cross-functional collaboration: Machine learning can forecast at very granular and frequent levels to support processes such as demand planning and S&OP processes that require planning by product and/or region. With ML, such forecasting can be done on a daily or weekly basis. Engaging in operational planning at that level allows planners to broaden their awareness of external influences (Figure 4) and include wide-ranging inputs in planning, budgeting and forecasting.

60% of financial decision-makers believe AI technologies have provided better actionable insights, 60% significantly improved speed of forecasting and 59% streamlined decision making.

With OneStream, The Carlyle Group can budget and re-forecast at both the legal entity and project level. The company has, as a result, improved visibility and traceability into allocations and budget version changes, with real-time viewing of budget impact. Through the self-service reporting and analysis in OneStream’s Financial Forecasting Software, business users can see the immediate impact of changes on plans and reports. The result? Submitting revenue/expense budget updates and reviewing the impact was reduced from 1 week to just 5–10 minutes. READ MORE

Finance-led Integrated Business Planning can drive some remarkable KPI improvements.

Finance-led Integrated Business Planning unifies business strategy with planning, budgeting and forecasting activity for all business lines and functions – providing one source of truth for the numbers. A trusted, common view of the numbers provides a robust baseline for agile decision-making and keeps all teams together. Those teams can then collectively work toward achieving the same corporate objectives while staying focused on specific KPIs. In other words, different teams maintain their independence while working in unison to achieve corporate success by leveraging the same trusted and governed data. The bottom line? Finance-led Integrated Business Planning aligns strategy intent, unifies planning processes and brings the organization together. The IBP process is a framework to not only address the C-suite needs but also help implement the business strategy and manage uncertainty to improve decision-making. The secret sauce is a collaboration between the different teams under a single view of the numbers unequivocally tied to financial performance. That’s how the C-suite gets value from IBP. Consequently, Finance plays a central role in successful IBP to help remove the departmental silos. Figure 7 outlines the five core elements of the Finance-led IBP processes.

The most efficient way to foster this collaboration is through a unified solution and data model that caters to the needs of the various agents involved. Below, Figure 8 shows how one solution that gathers all the capabilities under a unified data model is the most efficient approach to IBP.

1. Better use of cash and net working capital, better EBIT The speed in decision-making unleashed by coordinating all planning activities under one management structure drives direct results in financial KPIs. 2. Increased revenue and easier access to market share growth Product, demand and supply planning are tied within the IBP process, unlocking top-line pertormance opportunities. 3. Improved DSO and customer service levels The IP process optimizes inventory across the network to ensure no customer order is left on the table, increasing serviceability and clearing invoice payments. 4. Improved DPO and supplier collaboration Better orchestration between planning and sourcing activities triggers a faster supplier response and shortens the payment cycle times. 5. Better employee morale and significant productivity The enhanced control and clarity around planning activities and the linkage to strategic objectives make the planner's role highly purposeful.

Along with investing in new technology for the organization overall, almost all organizations are investing or planning to invest in new tech solutions to support finance functions specifically. The most common solutions they are investing in are:

Taking Finance Further requires thinking about new technologies that enable teams to make better decisions. And the results speak for themselves – financial decision-makers polled in 2023 are investing or planning to invest in technology that supports the Finance Office of the future in Figure 1 below.

Figure 1: Financial Decision Maker Outlook Survey Q1 2023

52%

43%

42%

CLOUD-BASED APPLICATIONS

AI / ML

ADVANCED PREDICTIVE ANALYTICS

BUDGETING / PLANNING SYSTEMS

Over half also believe Al has streamlined decision-making 59% and improved accuracy of forecasting 58% Almost no businesses state Al has not had a significant impact <1% or that it is too early to tell the impact <1% Nearly half expect real-time forecast updates 43% and one-third expect daily forecast updates 31%

Two-Thirds of Businesses Believe AI Has Provided Better Insights and Improved Speed of Forecasting

FREQUENCY OF FORECAST UPDATES

Figure 2: Financial Decision Maker Outlook Survey Q3 2023

Real-time Updates Daily Updates Weekly Updatess Monthly Updates Unplanned or Sporadic Updates

0% 20% 40% 60% 80% 100%

43%

31%

21%

<1%

0% 20% 40% 60% 80% 100%

<1%

58%

59%

60%

It has provided better, actionable insights It has significantly improved the speed of our forecasting It has streamlined our decision-making process It has significantly improved accuracy of forecasting* It's too early todetermine the impact It has not had a significant impact Other

WAYS AI AFFECTED FINANCIAL FORECASTING AND DECISION-MAKING

Enterprise Finance AI

Figure 4: Sensible ML Feature Library Page with External Variables

Figure 3: Sensible ML Dashboard

Al has also had a positive impact on forecasting and decision-making among businesses.

60%

Increased strategic decision-making: Ultimately, all the benefits gained through AI-powered operational planning result in better strategic decision-making. By analyzing more data faster and with better accuracy, analysts have more time to take a more comprehensive approach to various possibilities and their potential impacts on the company’s financial health. This approach gives Finance leaders visibility into how various scenarios would impact cost of goods sold (COGS), gross margin, EBITDA, cash flow and other important financial metrics. When leaders are navigating uncertainty, these KPIs are critical. All leaders want timely, accurate insights to increase performance efficiently and effectively, and AI-powered operational planning will help leaders do just that. Ultimately, AI is driving better insights and decision-making within businesses that are utilizing it. In the Financial Decision Maker Outlook Survey from Q3 2023, it was noted that AI was driving better actionable insights, improving the speed of forecasting and streamlining decision making (figure 5). Al has also had a positive impact on forecasting and decision-making among businesses. Financial decision-makers believe Al technologies have provided better actionable insights (60%), significantly improved speed of forecasting (60%), and streamlined decision making (59%). Additionally, automation from Al has enhanced decision-making speed (49%), data insights (48%), and the quality of output (48%) for half of businesses.

49%

Additionally, automation from AI has enhanced decision-making speed by 49%, data insights by 48% and and the quality of output by 48% for half of businesses.

For one-third of businesses, each of these benefitshave resulted in cost savings: faster decision-making 36% improved quality of outputs 34% and improved data insights 34%. Most financial decision-makers 81% also believe AI technologies have been helpful in automating key financial processes, and they are better able to predict and manage risk 73% Additionally, AI has fostered more collaborations between groups 58% with finance acting more as a strategic partner. Specifically, the role of the CFO has evolved to be more strategic 55% and more involved in IT decisions 48%

Figure 5: Financial Decision Maker Outlook Survey Q3 2023

FINANCIAL BUDGETING & FORECASTING

Why not? Well, change is constant, and organizations require agile planning processes to continually monitor performance and recast operational plans. FP&A teams ultimately require the ability to support top-down, bottom-up, driver-based planning; rolling forecasts; predictive analytics; and other advanced planning techniques. Why? These tools help fuel collaboration with operational business partners to identify opportunities and risks and guide decision-making. How? By monitoring the pulse of the company both holistically and at the business-driver level. As one example, the tools provide visibility into how sales, production, price, insurance or tax changes could affect profitability and future plans. Leaders in financial forecasting are investing in technology, and more specifically cloud-based applications and AI and Machine Learning, to enable this visibility (figure 6).

Half of Organizations Are Currently Implementing New Tech Solutions to Support Finance Functions

FP&A-LED INTEGRATED BUSINESS PLANNING

Figure 6: Financial Decision Maker Outlook Survey Q1 2023

0% 20% 40% 60% 80% 100%

42%

43%

52%

Cloud-based applications Al and Machine Learning Advanced predictive analytics New budgeting/planning systems New financial close and reporting systems New ERP/Accounting system Blockchain or digital currencies Unsure

TYPES OF TECHNOLOGY BEING INVESTED IN

0% 20% 40% 60% 80% 100%

43%

48%

YES We are currently implementing new tech solutions to support finance functions YES We plan toinvest new tech solutions to support financefunctions in 2023/2024 NO We are not currently investing in new tech to support finance functions and don't have plans to do so in 2023/2024

INVESTMENT IN NEW TECHNOLOGY TO SUPPORT FINANCE FUNCTIONS

26%

29%

38%

Rigid plans and budgets aren’t useful.

Figure 7: The Integrated Business Planning Process

BUSINESS STRATEGY

DEMAND REVIEW

SUPPLY REVIEW

FINANCIAL REVIEW & RECONCILIATION

MANAGEMENT BUSINESS REVIEW

Integrated Business Planning

• Review main product/ customer profitability • Review NPIs and Eols

• Review demand trend and market opportunities • Include Commercial assumptions

• Review major supportability issues, scenarios, investment options and inventory position

• Review financial, cash flow and growth • Review cost/benefit of investments and scenarios

• Review e2e scenarios and impacts on customer satisfaction, asset utilization and cash flow

PORTFOLIO REVIEW

REPORTING & ANALYTICS

AOP & BUDGETING

STRATEGIC PLANNING

CONSOLIDATION (ACTUALS)

HR, CAPEX PLANNING

S&OP / IBP PROCESS

AOP & BUDGETING

FINANCE PLANNING

DEMAND PLANNING

SUPPLY PLANNING

EXECUTION

SUPPORT FUNCTIONS

SUPPLY CHAIN EXECUTION

PRODUCT MKTG & SALES

CASE STUDY

conclusion

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NO We are not currently investing in new tech to support finance functions and don't have plans to do so in 2023/2024

Blockchain or dig. currencies

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