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Anaplan Planning 2030
  • Anaplan
   

Planning, Forecasting, and Budgeting: Outlook to 2030

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While none of us can predict what the future will bring, we have a responsibility to consider future possibilities and prepare for them accordingly. For the finance sector, this means working smart to get the right technology and people and being agile enough to respond to inevitable disruption ahead.

Without a clear vision and strategy for finance in the digital-dominated world, that is unlikely to happen. It's time to take a step back and make sure your plan for getting there is clear.

Planning, budgeting, and forecasting - present inevitable challenges to many organizations, regardless of industry or size. Planning is an essential part of managing both financial and operational performance, and it may significantly impact a company's overall success, particularly in the competitive business world of today, where disruptive competitors are joining even the most established sectors. Planning, particularly the annual budget process, is viewed as cumbersome and time-consuming despite its supreme significance.

Budgeting covers revenue, expenses, potential cash flow, and debt reduction and outlines how the plan will be carried out month by month. A business will choose a fiscal year and develop an annual budget. Depending on actual income levels, the budget can also be adjusted. It may also compare real financial statements to the budget to assess how near it is to be met or exceeded.

Using historical data and existing market scenarios, forecasting provides estimates about the amount of money an organization will generate over the following few months or years. Forecasts can be modified as per the availability of new information.

An IBM report states that 81% of CFOs in 2015 considered optimizing their planning, budgeting, and forecasting as crucial business goals.

However, a few years later, just 14% of CFOs claimed that their business operations were technologically "optimal," with systems allowing data-driven decisions. Change is undoubtedly overdue. Planning that is dynamic and built on feedback from across the organization gives enormous opportunities to increase process efficiency and business intelligence, according to forward-thinking business leaders.

These organizations also understand the significant business value that modern planning solutions add to business operations, marketing, sales, supply chain management, HR, etc. The organizations can better coordinate their actions and see how their decisions impact the organizational activities.

Once strategic planning is done, it is important to develop guidelines for the budgeting process that address sustainability aspects and their link to the implementation of business plans and growth. Further, set performance budgets for each business function and deliver top-down and bottom-up financial and operational plans.

After planning and budgeting, assess performance and enable a realistic outlook of existing and expected business performance. This forecasting process will result in timely management decisions and corrective actions.

Key Challenges in the Process

  • Difficult to create a standard approach for integration as PBF processes vary across businesses.
  • No awareness of sustainability and the value it creates for business.
  • Limited progress due to failed strategy of overestimating budget.
  • A rigid process leads to delayed outputs.
  • Inaccurate assumptions and tedious manual inputs.

Planning and budgeting for line-of-business managers might occasionally seem like little more than a sporadic time-waster with little payoff. They may feel under constant pressure to do more with less and be besieged by specific information demands.

As a result, it leads to a failed strategy of overestimating budget requests in the hope that budgetary allotments will be insufficient to cover their requirements. These inconveniences, however minor in comparison to the missed opportunities can result from rigid planning and forecasting, especially during volatile economic phases.

Large organizations may have million-dollar budgets for business applications but they struggle with actual lines of business, including point-of-sale or manufacturing floor equipment that generates gigabytes of real-time updates, ERP, supply chain, HR, and sales planning.

Many organizations use business intelligence or analytics tools as layers to those functional applications to make strategic decisions. These tools help transform data into appealing dashboards and accurate reports.

The two layers continue to be disconnected, nevertheless. All of those enterprise apps may release data at different rates, in different file formats, or even in response to entirely distinct queries.

Therefore, it cannot be easily shared across other departments or functions, let alone with analytics tools. Instead, line-of-business managers must manually compile the information they require into databases or spreadsheets before using it to feed BI reports.

As a result, there may be an increase in spreadsheets containing frequently outdated or conflicting data (needless to mention a lot of extra effort and time).

Delve into this Whitepaper to explore what collaboration between supply chain and finance can unlock using anaplan planning

Eliminating the mess with Anaplan

This is where Anaplan comes to light replacing the mess between functional applications and analytics tools. You can develop a shareable, real-time model of how your business operates with Anaplan's cloud-based planning tool. Scenarios can be created and tested to reveal blind spots and untapped opportunities. The models allow you to quickly adapt strategy to desired outcomes by directly connecting operational data to BI dashboards and analytics.

Consider a chain of department stores that is trying to maintain its profitability in a rapidly-evolving retail landscape. Each function has a unique business procedure that is automated by various application sets.

Demand planning, which involves predicting what customers are likely to want over the next year; supply chain planning to involve locating and scheduling the delivery of the accessories, home goods, and clothes it will sell, human resource management to manage store associates, warehouse workers, merchandising to organize marketing campaigns, facilities management, which keeps stores attractive and safe, incentive planning to encourage salespeople, and customer service to cater to buyers needs.

Of course, each of these functions has a specific enterprise application, or perhaps several. Here’s how the Anaplan platform helps in developing, testing, and fine-tuning the assumptions and steers the business toward reducing risk and maximizing profit.

Anaplan with Scenario Planning: What’s on the Table?

CFOs cite analytics as a significant tool for finding new growth prospects, supported by the integration of internal company data with data of competitors and external markets. Additionally, CFOs can harness the potential of agile scenario planning and intelligent forecasting with robust data to assess acquisition opportunities.

When aligned with external data sets, such as macroeconomic forecasts, scenario planning can be more successful in simulating a broad influence on the organization. Spreadsheet-based scenario planning can often become challenging due to the sheer amount of data and the requirement to make changes rapidly while also understanding their effects.

Finance users require a scalable and adaptable technological solution to swiftly predict and evaluate the business impact of a variety of situations.

Organizations can build comprehensive, thorough scenarios using Anaplan that consider all of the important internal and external data and factors that impact the business. The key areas affected by a change in a scenario variable are immediately updated, keeping all plans and projections continuously up to date.

Business leaders can experiment with the effects of both internal and external changes, such as a new cost-cutting efficiency or a disruption in the supply chain. Anaplan provides you with a quick overview of how these modifications affect various organizational aspects and business outcomes.

Preparing for the Future: Focus on the top and at the bottom

Aligning top-down financial goals with bottom-up plans is a crucial attribute of effective budgeting and forecasting. Some organizations set annual top-down targets and then delegate the budgeting process to finance with a directive to achieve those goals.

Other organizations demand thorough bottom-up plans that are then adjusted at the top to reflect the complete company data in order to achieve strategic goals. Both of these strategies don't represent a practical way to achieve superior planning.

Modern businesses require versatile planning, budgeting, and forecasting capabilities that span processes across the organization- something that legacy systems are unable to provide. By connecting people, data, and plans across all organizational functions, organizations get a 360-degree view of what is happening, why it is happening, and where they are heading to.

Organizations can run real-time reports and assess scenarios using advanced insights, which leads to better business decisions and results. Organizations can develop the flexibility and teamwork required to transform constant change into a competitive advantage by embracing connected planning.

By 2024, 70% of new financial planning and analysis projects will become extended planning and analysis (xP&A) projects, expanding their scope beyond the finance domain into other areas of enterprise planning and analysis, as per Gartner's 2020 report on Strategic Roadmap for Cloud Financial Planning and Analysis Solutions.

Real-time intelligence, continuous forecasting, and cross-functional planning are essential to your organization's success in the new normal. However, not all financial planning systems are capable of delivering such capabilities.

Predictive Analytics to be the norm: The Game Changer

Over the past ten years, there has been an explosion in corporate data, creating new opportunities for insight and foresight. One of the many large caches of granular data that can help in focusing and fine-tuning budgets, projections, and plans is supply chain management.

Other sources of granular data include sales, inventory, search history, and customer relationship data. However, with such a scale, manual manipulation is just impractical; instead, advanced tools such as AI and ML are highly reliable & beneficial. Is significant adoption of predictive analytics possible, given the low acceptance of several modern accounting processes like rolling forecasts and scenario planning?

An FSN’s 2021 research reveals that only 19% of firms rely on forecasting methods, 13% employ zero-based budgeting across the organization, and 13% use scenario planning to enhance their planning, budgeting, and forecasting (PBF) process.

Utilizing the system and process requirements for these modern accounting approaches is a need for progressing to predictive analysis (standardized, automated, and verified data, effective PBF systems). It seems difficult for the survey's three-quarters of finance executives to expect to be adopting advanced tech practices like predictive analytics, AI, and ML before 2030.

Finance leaders aspire to have predictive analytics standard practice for 75% of firms by 2030, but a quarter still doesn't believe they'll need it or believe it's not feasible by then. However, they also bring a checklist of prerequisites that must be met before predictive analytics may be properly applied in the PBF process. The most important of these is the need to understand how the solutions they employ function internally.

Explainable algorithms that can be modified inside the function itself are desired by finance functions trying to integrate predictive analytics into their planning, budgeting, and forecasting processes. Also, they want the solutions to be as simple to use and create as existing business intelligence tools.

Additionally, they want to be able to connect the predictive models to external market data and financial data. They want all of this included in forecasting software for better business performance.

With modern technology, AI will revolutionize analytics by greatly enhancing their power. Analytics software only offered descriptive analytics ten years ago. Solution providers were developing predictive analytics as the volume of data generated expanded.

Data analytics programs are changing and becoming more complex as AI advances. Prescriptive analytics is the subsequent stage in the development of data analytics, drawing on earlier iterations to show potential outcomes.

Skills not headcount: Achieving the next frontier in finance efficiency

For the finance function to achieve any of its long-term ambitions for forecasting and planning improvement, it needs the right tools and the right skills. The latest survey by FSN showed that data scientists, business partners, and systems accountants are all being prioritized over FP&A professionals, and specialists in statutory reporting are least in demand, languishing a long way behind all the other functions in the investment queue, despite new statutory reporting requirements.

Despite the present skills gap that many industries are experiencing, the financial function gap is and has been a very serious problem. 42% of finance executives raised concern in a 2019 study that their lack of digital proficiency would hinder them from using new technology over the next three years.

Three years later, 73% of financial executives claim that without major specialization and upskilling, they won't be able to achieve their goals. A shortage of financial skills, according to 45% of respondents, will hold companies back, and half acknowledge that automating finance operations alone won't free up enough time to achieve their goals.

Concluding Note

Align Value Drivers on an Organization-wide basis

Review data structures & requirements to ensure that the PBF process is developed around data linked to business value drivers that promise strategy in the longer run.

Incorporate External Data when required

Data on consumer demand, supplier info, economic or government data, and competitor info hold a lot of significance. They should be incorporated into the PBF process to drive accuracy and flexible scenario modeling.

Agree on performance & success measures

The enterprise must have a clear understanding of what comprises successful planning, budgeting, and forecasting. Does sticking to the budget imply you missed an opportunity? Does the forecasting process ensure accuracy?

Instill better data governance

Eliminate functional silo-based data ownership and establish clear accountability for data across the company. This will produce a "single version of the truth" and clean, consistent, full data around important processes that have been identified.

Optimize Rolling forecasts

A more current picture of the expected performance of the company in relation to strategic goals is provided by monthly rolling projections that are in line with the operating model of the company. This facilitates quicker decision-making and resource reallocation where the forecast deviates from the target and lays management attention on the future.

The coordination of technology, business procedures, and best practices is necessary for the successful deployment of a planning solution. As a leading Anaplan partner, we help you with your end-to-end Anaplan needs by creating and implementing personalized connectors, APIs, and ETL tools for your day-to-day business operations.

With Anaplan and its multiple integration models, we help you leverage the ‘connected planning’ approach and eliminate the spreadsheet data process. An organization can greatly enhance its financial and operational performance by aligning its PBF process with best Anaplan practices. And experts at Polestar Solutions help you choose the best practices and pave your way toward tangible results and maximized ROI.

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