Demand planning is mission critical for any organization because – when done well – projects the business growth potential by anticipating the expected demand to supply. That allows for optimizing inventories and rising customer satisfaction with better service. Traditionally, demand planning sits within Sales or Supply Chain organizations, supporting the S&OP process. But since it plays a key role in the core financial processes, forward-looking Finance leaders should be finding ways to unify demand planning with Finance.

With that in mind, this blog spells out the intersections between Finance and demand planning and describes the technology available to unify demand planning with financial processes.

Understanding Demand Planning

Demand planning is the first step within the demand management process (see Figure 1).

At its core, demand management represents an effort intended to match market needs with available resources. The demand management process often starts with a forecast analysis. That forecast is then enriched with inputs from Marketing, Sales, Product Development, Business Strategy and – of course – Finance to shape the demand plan. Customer orders (real demand) need to be managed and prioritized, that’s when the rubber hits the road. Finally, demand management is part of the S&OP or IBP process, an ongoing and collaborative process that ultimately helps the organization achieve better results and become more resilient.

The Value of Demand Planning for Finance

In many organizations, the relationship between the Office of Finance and demand planners is unrelated. But it shouldn’t be. Demand planners should get from Finance teams the top-down plans, financial objectives and budget figures to determine the aspiration and constraints. And – at the same time – demand forecasts can be of exceptional benefit for Finance teams.

In many ways, demand management directly or indirectly impacts the core financial processes. So why shouldn’t Finance teams benefit from using demand forecasts and plans as inputs? Those inputs can be used by Finance in many ways:

• Strategy Validation. Demand forecasts are a great way to validate strategy, especially when sales and financial objectives are too optimistic. Demand forecasts offers the Office of Finance an independent perspective built on market and business drivers.
• Financial Planning and Budgeting Accuracy. Demand plans feed marketing, sales and supply chain plans. Therefore it is a key input for planning and budgeting decisions around inventory levels, capex investments cash, spending and more.
• Profitability Analysis. Unifying the financial model with demand forecasting helps measure the P&L impact across the value chain.
• Reduced Bias. Some Finance teams feel obligated to create their own biased forecasts to meet top-down expectations and address margin and cash flow optimization pressure. Finance leaders can identify bias more easily when demand plans are incorporated into the financial planning and budgeting processes.
• Accurate Accounting. Demand plans offer a view of across a time horizon, helping controllers better predict cost, taxes and revenue allocations.
• More Credible Reporting. Finance teams can leverage the independent perspective that demand plans provide for both internal and statutory reporting. That ultimately adds credibility to financial statements.

Organizations that combine financial and demand planning can unlock the value laid out through the scenarios above (and others!). Rather than planning by siloes, organizations can take a systemic perspective to overall planning – to see the forest through the trees, so to speak.

A Unified Platform for Better xP&A

Unifying demand planning with Finance is one of the many advantages an xP&A solution brings.

According to Gartner, “by 2024, 70% of new financial planning and analysis projects will become extended planning and analysis (xP&A) projects, extending their scope beyond the finance domain into other areas of enterprise planning and analysis.” [1]

The Office of Finance can now benefit from new technologies that leverage financial and operational data with machine learning to realize the benefits outlined above. However, not every technology solution is the right fit to support a xP&A structure. Below are factors that Finance should consider when looking for a suitable technology:

• Unified Data Model. Not all solutions are technically ready to bring operational data at scale, so the solution must have a unified data model that caters to both financial and demand-related data.
• Data Management and Quality. The way the solution manages and ensures the quality and integrity in data is imperative to building one version of the truth and turning data into insights.
• Core Corporate Performance Management (CPM) Services. The solution must support the main needs of Finance teams. Having all CPM services in one platform enables strategy validation, planning and budgeting accuracy, profitability analysis, bias reduction, and more credible reporting.
• AI Services. The solution must deliver scalable AI capabilities for the Office of Finance and beyond. Machine learning in demand forecasting is helping organizations reach higher levels of forecasting accuracy (see Figure 2).

Conclusion

Finance leaders must consider demand planning as a powerful tool for driving better results. Why? Because it provides an independent view of the market. Only a single platform with a unified data model and machine learning capabilities can deliver the xP&A requirements to unify demand planning with Finance.

A good example of what’s possible is how Autoliv – a worldwide leader in car safety system – redesigned its core processes to unify consolidation, financial and operational planning to address market uncertainty. Autoliv now leverages machine learning in demand forecasting to increase granularity, reduce forecasting cycles (daily) and bring the cost down– something otherwise not possible without the use of artificial intelligence.

Learn more about how Autoliv leverages Sensible Machine Learning to improve financial and business results:

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In the previous blog post of this series, we covered why leaning on a truly single platform with an extensible data model is the most effective way to unify business strategy with planning activities across the enterprise.  The prior post also laid out the framework of a unified integrated business planning (IBP) model and identified the hidden costs for organizations that implement IBP built on fragmented tools and spreadsheets.

This final post of the series shows the benefits from an IBP journey and then digs even deeper. Why?  To show how an organization can maximize those benefits when the IBP implementation is underpinned by a single platform with an extensible data model.

Benefits of Unifying “Connected” Business Planning

The benefits an organization can expect from an IBP implementation are diverse. In the big picture, IBP can certainly improve financial and business performance. Figure 1 outlines some of the most remarkable KPI improvements.

The range of improvement organizations claim through those benefits can be substantial, too.  According to McKinsey & Company, “The average mature IBP practitioner realizes 1 or 2 additional percentage points in EBIT.  Service levels are 5 to 20 percentage points higher. Freight costs and capital intensity are 10 to 15 percent lower – and customer delivery penalties and missed sales are 40 to 50 percent lower.  IBP technology and process discipline can also make planners 10 to 20 percent more productive.”  McKinsey & Company also emphasizes the importance of keeping P&L owners involved in the IBP process.

Equally important to those benefits is the technology used.  What’s the advantage of choosing the right technology to support the IBP process?

Simply put, the choice of technology is pivotal for achieving the highest percentile of the benefit ranges. Yet many organizations undervalue the role technology plays in achieving better results.  Instead, those organizations live with sub-optimal IT architectures populated with point solutions, weak integration flows and uncontrollable spreadsheet usage. Those pitfalls only further emphasize why organizations aspiring for excellence should opt for a truly unified platform that covers the breadth of an IBP process.

Going for one platform with the right data integration model not only provides higher business benefits but also results in lower IT costs, frictionless collaboration among teams, more speed in decision-making, enhanced resilience to any changing condition (e.g., market disruptions, growth by acquisition) and less risk.

Maximizing the Value of IBP with One Platform

When one unified platform caters to the needs of integrated business planning, organizations can aspire to get the highest return of value from the IBP process. Having one platform that unifies business strategy with all planning activities, consolidation and reporting provides unmatched levels of performance. And this advantage is exactly what organizations get when choosing to support their IBP journey with OneStream’s Intelligent Finance Platform (see Figure 2).

OneStream’s Value Realization Report validates the platform advantage. The report details the benefits that adopters of OneStream’s Intelligent Finance Platform achieve across the different domains that pertain to corporate performance management: data management, close & consolidation, account reconciliations, reporting, and planning & budgeting.  According to the report, OneStream simultaneously generated value in four different areas:

1. Technical Debt (i.e.,difference between current state cost and future state costs.) One platform drastically reduces or eliminates certain technical costs. Those costs include administrator costs, hardware and data center costs, upgrade costs, data warehousing, third-party software to complement or enhance the applications (e.g., machine learning engines, inter-company eliminators, currency converters, etc.), disaster recovery costs and more.   
2. Effectiveness. Being more effective or making better decisions faster is possible by simply having information readily available at the right time and with the right level of detail. The use of one platform and one data model increases effectiveness significantly. Why? The need for continually copying, moving and reconciling data among different point solutions is eliminated.
3. Risk Mitigation. OneStream helps avoid costly mistakes caused by manual step errors and the lack of traceability and auditability. The full advantage comes by having full, direct integration with systems such as GL/ERP and other source systems.
4. Efficiency. According to OneStream’s Value Realization Report, “Planning and Budgeting takes less time for OneStream customers.  A customer that moved from a rudimentary Excel®based system to their first budgeting tool saw a revolutionary improvement of 95%. Customers who moved from another budgeting tool that was relatively sophisticated saw between a 10% and 25% improvement in the time they spent on budgeting after implementing OneStream.”  On average, OneStream users see efficiency improvements of 42%.

Data management is massively improved as well.  According to the report, “Customers improved their data management processes, delivering results between 98% improvement when moving from a complex system with several disparate systems and 10% when upgrading from a system that is already fully integrated but needs to take advantage of more fluid flow of data and information.” This improved efficiency ties directly back to the financial and business performance KPIs introduced earlier in this blog post (see Figure 1) – i.e., significant productivity gains, better use of cash, net working capital, better EBIT, revenue and market growth, better service levels and improved DSO, DPO and DIO.

Conclusion

This blog series highlights why current market conditions require new approaches to integrated business planning and why many organizations struggle to implement IBP due to three main challenges: lack of leadership support, organizational resistance and underestimating the technology needs. 

These challenges aren’t insurmountable, however, thanks to advanced technology solutions that truly unify business strategy with planning. And when organizations aspire only to excellence, one platform with a single extensible data model is the key to successful IBP implementations. 

OneStream’s Intelligent Finance Platform delivers in that regard. Its data-first approach to integrated business planning unifies the views of strategy, planning and performance – increasing the speed of decision-making and improving business performance.

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Discover OneStream’s Intelligent Finance Platform advantage here, and download the Value Realization Report

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As stated in our previous blog post titled “Why Is Integrated Business Planning So Hard?,” we examine why unifying integrated business planning (IBP) or connected planning processes enables organizations to ensure they take a data-first approach to all planning activities. Such a planning approach aims to unify business strategy with planning, budgeting and forecasting activity for all business lines and functions – providing one single version of the truth within a single, seamless technology platform and user experience.

A trusted, common view of the numbers provides a robust baseline for agile decision-making and keeps all teams together, collectively trying to achieve the same corporate objectives while staying focused on specific KPIs. In other words, the different teams maintain their independence while working in unison to achieve corporate success by leveraging the same trusted and governed data.

This approach is underpinned on a single technology platform that can manage planning, budgeting & forecasting (PB&F), consolidation and reporting all in one place – without the need to duplicate data or otherwise maintain different solutions. The advantages of this approach are many:

• Trust in the numbers. While every function plans at a different level of granularity, all can be tied back to financial metrics and strategic objectives because all functions are using the same data within the same platform.
• Leadership buy-in. Using one version of the numbers is pivotal to managing business performance. No substitute exists for a single accurate picture of plans and performance, so hardly any CEO and CFO would turn away from this advantage.
• Improved collaboration. One key aim of unifying business planning is to help reach consensus among all planning parties. When teams no longer need to collate and compare plans, collaboration flows and allows consensus planning to happen faster.
• Instant response to events. When the same data is used for forecasting and consolidation, actuals can be served to support shorter forecasting cycles (daily, hourly) and what-if simulations. In current volatile times, this capability offers a true competitive advantage.
• Faster IBP process implementation. If one of the IBP fundamentals is “one set of numbers,” why not set it as the single most important requirement for any IBP process implementation? Having one single technology and data model is a unique way to obtain “one set of numbers.” When this requirement is met first, the IBP process can deliver faster business integration, establish a superior planning structure and begin to model the right culture and behaviors.

Leading the Change

Intelligent Finance teams lead business planning unification and foster collaboration across the organization. While the teams oversee and facilitate the planning activity, doing so should not suppress the detailed planning required between and by the different business lines and functions (e.g. Supply Chain, HR, IT).

Instead, all planning activities should focus on a central Finance planning capability that orchestrates and aligns data, strategy, processes and people across the different business units and functions (see Figure 1). This central capability is simple to understand when the main mechanisms to show market value and performance against strategy goals are financial artifacts such as P&L, balance sheet, and income and cash statement.

Unfortunately, most options for connected planning, integrated business planning are simply not built for this purpose.  Why? Rather than relying on a truly unified data model, Finance and IT teams are forced to connect plans across systems and spreadsheets by moving and reconciling data. Those processes, in turn, add material risk and cost to integrated business planning efforts.

In other words, true unification matters – a lot.

How to Unify Business Planning

Unified business planning is anchored on 3 key principles:

• Principle of collaboration. Team collaboration starts with adopting a clearly communicated vision, setting the expectations around teamwork, and defining KPIs aligned to strategic objectives and financial attainment. Finance should orchestrate and foster collaboration and support all teams. Ideally, a leadership role – one that reports to the CFO – should be established to orchestrate all planning activities. 
• Principle of simplification. Simplification occurs as a result of process step elimination, minimization and automation. Planning processes should be challenged by removing complexity, redefining measurements and ultimately automating tasks. When a unique view of the plan is instilled, the need for file version control, data reconciliation and validation is drastically reduced or eliminated.
• Principle of technical unification. This principle is the single most important precept to follow in a unified business planning approach. Achieving technical unification calls for breaking away from suboptimal technology solutions and spreadsheet patching. Instead, such unification requires considering a solution capable of managing both financial and operational forecasting, planning and budgeting processes while providing financial consolidation, reporting and analytical tools all in one place – and doing it with speed and scale (see Figure 2). When a single solution is used to manage all these processes, bringing people together and simplifying the process becomes easier.

These principles not only provide a robust foundation throughout the IBP journey, but also facilitate the adoption of technology that truly unifies people and processes.

Unified Integrated Business Planning Model

A data-first approach to integrated business planning unifies the views of strategy, planning and performance, increasing the speed of decision-making.

Figure 3 shows the model for unified business planning platform. In light gray, the figure shows the key processes that must be part of the same platform under one data model to reap the benefits of this approach. The figure also displays a representation of an IBP process with a closed loop between planning and execution – a loop that remains aligned to the business strategy because everything relies on the same data and technology.

Unify Integrated Business Planning, or Face the Hidden Costs

Unifying integrated business planning brings data and people together, helps the organization model the right behaviors, and removes the friction of traditional technology silos and spreadsheets.

Today, Finance leaders have the organizational influence to lead an IBP process based on a unified approach. However, unifying integrated business planning requires one single platform and extensible data model, not an integrated set of connected modules from the same vendor. This approach offers the most effective way to unify business strategy, planning and performance.

By not taking a unified and data-first approach to IBP process implementation, organizations face the hidden costs of dealing with archaic and fragmented technology:

• Technical debt: Cost of maintaining outdated or obsolete technologies.
• Reduced efficiency: Costly mistakes derived from reconciliation and manual touch-points.
• Less effectiveness: Organizational friction and higher elapsed time between planning and execution.
• Higher risk, opportunity loss: Result of slow, biased decision-making.

Learn More

To learn more about unified business planning, watch this video.

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Planning for business is becoming increasingly more complex, requiring new approaches supported by sophisticated planning technologies.  Recent research even indicates that business strategy, financial and other planning activities (operational, HR, sales, etc.) are better together.  Thus, Connected or Integrated Business Planning (IBP) has become a hot topic for leaders who want to thrive in this challenging business context.  But why is IBP so hard to implement?

This blog series looks to answer that question by diving into why companies aren’t successful when adopting Integrated Business Planning.  In doing so, the series explores why the CFO is best positioned to lead the change.  Part 1 explores why Integrated Business Planning is difficult.

A Broken Mirror

Connecting or integrating business planning activities across the enterprise is not a new idea.  In fact, concepts like xP&A aim to respond to this need from a technology perspective, and terms like Integrated Business Planning have been around for decades.  However, today’s unique market volatility combined with failed attempts at connected planning shows why the topic needs to be elevated to the C-level.

Organizations encounter various obstacles when implementing an Integrated Business Planning process. And those organizations invest significant resources and time trying to overcome challenges and get the process to work.  Amid a long list of challenges, 3 stand out as the most difficult to overcome:

1. Leadership skepticism and misalignment around the IBP process.  As Oliver Wight rightfully points out, “one set of numbers” is a stepping stone in a well-deployed IBP process.  However, getting there isn’t easy.  But why?  First, the current state of technology and data strategy in many organizations doesn’t support an IBP process.  Second, some might be uncomfortable with this better reality: the visibility that comes with one view of the numbers can surface human bias, shortcomings or resource buffers that some leaders want to keep hidden.
2. Culture and organizational change can’t do it alone.  Companies structured in silos fail to connect strategic goals with planning, model the wrong behaviors (conflicting targets, biased assumptions, etc.) and force a fragmented planning approach.  How does all this affect the IBP process implementation?  Well, adjusting the culture and behaviors is hard work, as well as setting up a solid management system and implementing horizontal roles to coordinate planning activities across silos.  This process requires an enormous effort in culture change, and it doesn’t stick in the long term:  organization and culture tend to mold and deform over time in response to leadership changes or strategic direction shifts.  Further, today’s volatile business environment requires unparalleled speed in decision-making that can’t be held up by sluggish changes in governance and organizational design.
3. Ignoring the technology trap.  Having one technology for all planning is a complex endeavor. Finance planning, business unit planning, sales & operations planning, workforce planning (to name a few) are all processes with different goals, data structures, units of measure, mathematical foundations and needs.  Even if functional technology is in place to handle these different planning needs, scalability becomes an issue when the solutions are exposed to massive amounts of data.

So…what are the options?  Well, many of the solutions out there cannot adapt to current needs due to being made of multiple modules that must be integrated or simply not having the depth and breadth required to support varied planning needs.  The alternative, then, is spreadsheet abuse that’s slow, laborious and prone to error.  And those organizations that manage to integrate all these modules from different software vendors do it at a high cost and effort, living up with an infrastructure that doesn’t scale and a tremendous technical debt.  In other words, the alternative is high RISK and high COST.

Since culture change is never easy and most technology can’t address the needs of truly unified planning, leaders are discouraged from embarking on an IBP journey and stall with sub-optimal processes and technologies.

This sub-optimal status often means a higher impact from risks and uncertainty due to a sluggish decision-making process.  Ultimately, that impact translates into the loss of business opportunities and a higher cost of doing business.

A Closer Look at the Technology Trap

Even with strong alignment and commitment around the IBP process, a closer look into the problem shows that organizations struggle to achieve the promised benefits for a specific reason.  Primarily, a consensus among planning activities that effectively links strategic & finance goals with financial and extended planning (xP&A) is complicated when technology isn’t fit for the task.

The Pulse Survey launched by BPM Partners in 2021 (Figure 1) displays some of the main challenges an organization can face with budgeting and planning activities:

Collectively, such challenges are strongly correlated to the flawed technology solutions that organizations use to support these processes.  

Often, many organizations undertake the implementation of IBP from a process and organizational standpoint, leaving the technology discussion for later.

However, if one set of numbers is a non-negotiable in IBP, why not address the technology trap for starters?  Wouldn’t collaboration be easier with a common foundation of data and information?  Wouldn’t it be easier for top leadership to execute flawlessly when all planning is based on the same numbers?  Why wait for a perfectly fine-tuned process when the right technology can accelerate the adoption of IBP?

There’s Another Way

When business planning isn’t unified, the leadership team can’t really get quality insights fast enough to improve the business performance.  Because planning is a cornerstone to budgeting and forecasting processes, both are impacted when the planning processes are carried out in a containerized way supported by inferior technology.  The different departments and functions suffer the consequences of a fragmented planning approach.

Despite the many attempts to join and synchronize all planning activities, these planning processes remain disconnected because they rely on different technologies and systems that cannot provide a common data structure.

But a (better) way forward exists, one where the CFO leads the change by implementing a collaborative planning approach with business lines and other functions.  Whether that occurs through xP&A, integrated business planning or connected planning, ultimately what CFOs really need to do is unify business planning.

By unifying IBP or connected planning processes,organizations ensure they take a data-first approach to all planning activities.  Such planning approach aims to unify business strategy with planning, budgeting and forecasting activity for all business lines and functions – providing one single version of the truth.  That single version is verifiable and certified in just one technology platform.

Learn More

Learn how to unify Integrated Business Planning in our next blog:

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What if Finance could proactively drive business performance before month-end?  And do so without the traditional pain points of trying to create and maintain complex reports?  These questions have never been more relevant since traditional financial processes that rely heavily on stable business conditions no longer cut it.  To earn a coveted seat at the decision-makers’ table and be proactive within today’s more volatile environment, Finance must move beyond the static financial processes associated with enterprise performance management (EPM) software.  How?  By avoiding bad analytics and leveraging financial signaling to drive operational analytics, Finance can anticipate and react swiftly to disruptive markets and conditions.

Don’t Be a Victim of Bad Analytics

Most Finance professionals are likely familiar with falling victim to bad analytics, especially the feeling that comes with having all the information needed to predict future market conditions, but being held back by the EPM technology.  While the thought of advanced analytics often conjures sci-fi images of robots and flying cars, such analytics are more of a reality than a pipe dream.  Leveraging quality operational analytics and unleashing the goldmine of data Finance is sitting on doesn’t require an advance computer science degree either.  Rather, enabling useful insights with the proper technical enablers is key to driving financial results proactively instead of reactively.

In my previous role as a financial analyst, I was always frustrated by the wealth of unused data at my fingertips, be it that the data was inaccessible or just too large a dataset for one person to sift through.  The “A” part of “FP&A” often felt like the biggest challenge in the role.  Instead of being analytical, I was often faced with looking backward wondering why I couldn’t anticipate events that the data should have alerted on well before month-end.

But the main thing holding me back from truly being predictive wasn’t lack of access to data or a limited data set.  The culprit was the time and technology available to do the analysis.  In essence, I was spending more time as a glorified data wrangler and spreadsheet jockey than as a true analyst.  I may have become a professional Excel® formula writer, but a huge missing piece prevented me from truly being proactive in my job.

Unleash the Power of Finance by Leveraging Financial Signaling to Drive Operational Analytics

Leveraging operational analytics and financial signaling in my financial analysis role would have truly been key to flipping a reactive role into a proactive one – ultimately elevating my role to valued business partner.  But how?

Well, to start, financial signaling (Figure 1) is the process through which Finance teams can finally harness the vast amounts of daily and weekly transactional and operational data from across the organization.  By deciphering the hidden signals with large volumes of data, FP&A teams can help guide organizational leadership to act midstream and impact the financials – all before month-end.

Figure 1: Using financial signaling enables quicker and more reliable decision-making based on data

What does financial signaling have to do with advanced or operational analytics?  Well, some sort of tool is needed to analyze and visualize what financial signaling is revealing through regular data updates.  Financial signaling enables users to intake data on a regular basis, but the advanced analytic framework must be in place to make sense of the data and publish it in a way that can be shared with leadership and other decision-makers.  Thus, using financial signaling allows for quicker and more informed decisions (Figure 2) that help an organization proactively drive financial results instead of looking backward at month-end wondering why things turned out the way they did.

Figure 2: Financial signaling enables effective reporting and analytics by being a forward-looking process

Examples of Financial Signaling Driven Advanced Analytics

While financial signaling clearly benefits the Office of Finance, some real-life use cases for this functionality offer even more insight.  Here are just a few options for leveraging this functionality:

• Corporate Finance: Financial signaling allows for generating and tracking performance against budget and forecast data, AOP, strategic plans and long-range plans. Predictive capabilities can also be used to spot potential disruption before it strikes and capitalize on opportunities.
• Operational Finance: Financial signaling allows Finance to partner with Sales & Operations Planning (S&OP) partners and processes to generate, track performance against, and update the sales and operations plans that drive the supply chain and operations planning for the year.
• Divisional Finance: Financial signaling allows for tracking daily, weekly and monthly metrics relevant to the business while staying in step with corporate financial metrics and goals. Finance can also track goals against strategic initiatives and the sales–product mix.

Conclusion

Finance must remain agile and adaptable in the face of increasing market disruption and increasingly faster business speeds.  To do so, Finance must deploy and utilize operational analytics in a way that allows for better, faster and more accurate forecasting.  To answer the question of how to proactively drive performance ahead of month-end, Finance can leverage financial signaling for faster and more frequent data analysis to make sense of and publish the data in a format that can be quickly and effectively shared with leadership.  That functionality is the key to driving strategic financial goals and ultimately maintaining Finance’s partnership with key stakeholders within the business.

Learn More

Want to learn more about leveraging financial signaling and advanced analytics to elevate your financial processes?  Check out our eBook on Advanced Analytics to help your Finance team lead at speed.

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To keep up with market volatility, business leaders must take two key steps.  First, leaders must promote demand planning as a business-critical process from the depths of the back office.  Second, leaders must better equip those who do the demand planning with new approaches and tools that improve the forecasts used in the strategic decision-making and Extended Planning and Analysis (xP&A) processes.

Aside from the immediate impact on revenue, poor demand visibility over the long term leads to risks from decision-making based on inaccurate data and a lack of confidence in xP&A processes.  Why?  Because for business leaders, making well-informed decisions in today’s volatile climate can’t be hindered by obsolete processes and technology, especially if the sheer amount of data available can’t be leveraged.

Whatever changes arise, demand planning helps organizations adapt.

What Makes Demand Planning So Hard?

Understanding demand in today’s volatile business climate has become increasingly difficult for organizations.  For instance, many business leaders struggle to understand demand elasticity (i.e., how demand reacts to a price change).  A good understanding of demand may help adjusting prices, but the majority can’t forecast demand accurately and will therefore attempt to hold on by squeezing productivity while battling increasing costs.  Smaller companies, however, may not have the option to increase prices due to larger, more cash-flush competition suppressing the price.

Regardless of size, for many leaders, demand forecasting is critical but generally lacks transparency when profit margins narrow to unbearable levels.

Demand planners can provide forecasts and insights on demand elasticity that then enable leaders to draw better demand shaping and demand shifting actions.  So why do companies struggle with demand predictions?

Ask any demand planner and he/she will tell you that possibly the most frustrating part of the job is making forecasts that no one uses or follows. Lack of accuracy and lack of speed in delivering meaningful forecasts are the two most frequent reasons why internal stakeholders may not trust their output.

Here are some of the most common challenges facing demand planners who are trying to increase the speed and accuracy of forecasting:

• Complex and different data inputs for the models – Manual inputs to the forecasts are provided in different non-compatible formats, whether it’s spreadsheets, paper-based reports, flat files, or other types. Meanwhile, automated system inputs come from different systems underpinned by different data models, which requires a strong effort in data mapping and conversion (e.g, data quality).  Consolidating all these inputs drives additional complexity and the use of different tools.  Why?  Often, the tools at hand are not equipped with the capabilities required to blend this mix, so the demand planners need to “glue it all” in a spreadsheet to produce the forecast.

• Restricted data conversion and limited reach from the forecasting models – First, with different input sources, the data is commonly not homogeneous, leading to poor data quality. Different systems apply different aggregation formulas and date formats, not to mention the different use of commas and zeroes.  And while machine learning forecasting is promising, such forecasts have been traditionally limited in scale.

What’s the impact to the demand planner in all this?  Ultimately, once the data has been prepared, the forecasting models available to the planner can hardly address the needs of the current business climate.  The pace of change is just too great.  And there is more to add:

• Culture and organizational structure lead to inadequate practices – In many organizations, demand planning (hence forecasting) sits within the Supply Chain function, and responsibility gets pushed down to lower ranks who have no visibility or insights into product demand. Additionally, organizations with a strong budget culture, even if executed well, may diminish the correct use of demand planning forecasts.  Why?  Well, even if forecasts are accurate, they ultimately get modified to fit the company’s budgetary expectations.

• Poorly implemented business planning processes lead to ineffective use of the forecast. In the S&OP process, the core purpose is to reach a consensus among sales, supply, and demand.  The demand forecast is a cornerstone in an effective S&OP exchange, but if this process isn’t followed or implemented properly, the value of the demand forecast gets curtailed.

5 Key Considerations for Demand Planning – At Speed with High-Level Accuracy

Certainly, the above challenges aren’t new, but they stand out in current unstable market conditions.  Every effort to improve demand planning will therefore help the business be more competitive and make better use of cash and resources.  What’s the best way to improve demand planning?  Here are 5 considerations to look out for when aspiring to better demand planning:

1. Adopt a holistic approach to planning and secure ownership from senior leadership.

Research shows that planning doesn’t work well in silos – doing so narrows perspective, creates redundancy, breeds the wrong behaviors, and blurs the vision.  In essence, it’s like being guided by a map in pieces.  This effect doesn’t remove the need for deep planning per area.  Rather, it all must be unified so that, when operational planning is seamlessly interlinked to financial planning (xP&A), demand planning is elevated and becomes an indispensable activity that drives business performance at a corporate level.  The CFO should ideally own the xP&A process and stimulate the organization with a culture of collaboration and no finger-pointing.  No one on the team should be shy about bringing this point forward until it’s addressed!

2. Seek goal alignment among participants.

Because every function has different and sometimes conflicting objectives, demand forecasting becomes an accessory and not mission-critical.  Often, demand planners fail to connect with the stakeholders and listen for needs.  This failure is problematic because clarity regarding the intended use for the demand forecast is an absolute must.  Will it be used as input for marketing and sales planning?  Will it inform budget decisions?  Will it drive manufacturing production scheduling?

3. Anchor the forecast to the right data points.

Good data is hard to get in a timely manner, so demand planners are contented with suboptimal, easy-to-access datasets (e.g., sales bookings, sell-in ratios, manufacturing throughput, on-time in- full deliveries, etc.).  But the goal is to forecast demand, not sales or supply chain performance.  For example, shipments are not a true reflection of demand because they often fail to honor the customer-requested delivery date, so why not use that instead?  As another example, when building the constraint demand plan, is it fastened to the right financial data points?  Using substandard data points is a clear symptom that the technology itself is an inhibitor.  Accordingly, those looking to enhance their demand planning outputs must include the right demand data points in the design and watch for solutions that deliver those data points.

4. Select forecasting techniques that are a good fit with the business.

With the pace of change in the market, time is of the essence.  And with all the disparate input sources and judgmental views of the forecast, organizations tend to build overly simplistic assumptions to justify using a few standard forecasting methods.  But there’s no one size fits in forecasting.  In fact, overly simplifying the choice of models to use limits the accuracy of forecasts.  Choosing a method depends on what’s being forecasted (type of product), the availability of abundant and meaningful data (meaningful = relevance, granularity, veracity), the complexity and volume of causal factors required, and the time available to perform the task.

5. Appeal for one version of the truth.

Due to the fragmented nature of systems and organizational structures, many plans and viewpoints exist.  That makes it practically impossible to have one version of the plan or see what’s happening (actuals) in time to respond to volatile risks and opportunities.  To avoid those pitfalls, all parties should look at the same numbers, ideally under one solution that can handle disparate sources of inputs, upgrade data quality and combine different modeling methods (inclusive of machine learning).  A unified solution should also respect the identity of each business unit and business function by showing the information in ways that are meaningful to those identities: multiple product information grouping (e.g., by product family, SKU, territory, stock location, etc.), measure (i.e., unit, value, currency), multiple horizons and flexible intervals.

Conclusion

Business leaders who must drive better business performance can always ask themselves the following question: If demand forecasting accuracy increased by 1%, how much would it mean in terms of…

• Organic growth by reducing demand at risk?
• Inventory levels?
• Better use of working capital?
• Increased cash/reduced cost of capital?

The answers lie within the demand planning team!  And while there will always be a need for adding assumptions, achieving higher demand forecasting accuracy at speed must be a key business priority.

Learn More

To learn more about how OneStream can help improve demand forecasting accuracy, download our Sensible ML solution brief for Demand Planning here.

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As today’s Finance leaders learn how to best navigate global uncertainty, increasingly more organizations are turning to extended planning & analysis (xP&A) to propel rolling forecasting and collaboration between Finance and Operations.  At the forefront is a push toward a coordinated approach to artificial intelligence (AI)-enabled planning designed to achieve greater alignment between the strategic, financial, and operational levels within an organization.  But the promise of transforming finance and operational planning into one cohesive ecosystem has fallen short due to fragmented solutions leaving little opportunity for true collaboration outside of Finance.

At least that’s what you’ve been led to believe.

Leveraging AI and other technologies have opened new possibilities for Finance leaders looking to drive continuous forecasting in the xP&A world.  Accordingly, organizations of all sizes globally are leveraging AI to refine the rolling forecast process and increase business value.  Many of the same leaders, however, are not putting the same emphasis on measuring and improving collaboration across the enterprise.  Why?  Well, fragmented solutions cause misaligned technology and forecasting processes, eroding organizational collaboration.  And the level of effort to correct the imbalance can simply feel too steep.

Want proof?  Just think about all the times Finance teams have had to chase monthly forecast files from sales, HR, supply chain, etc., only to find out the provided files are incomplete or have some anomalies that require follow-up.

Sounds familiar, doesn’t it?  Whatever the case, it still feels like a waste of valuable time across all lines of business.  Guarantee this kind of collaboration isn’t the kind for which organizations strive.  But unfortunately, this world is the one in which most organizations live.

This environment is, however, one where AI can step in – especially amid the rise of xP&A – to reduce the level of effort needed to drive continuous collaboration with rolling forecasts.  How?  By automating siloed operating plans, speeding up the delivery of actionable insights, and aligning the Finance and Operations planning processes.

Without Organizational Collaboration, Rolling Forecasts Will Never Succeed

The forecasting process not only represents a core responsibility of the Finance function but also presents some of the most fundamental challenges as Finance must coordinate with other functions and departments in the organization.  This core process requires Finance to leverage critical data points from Sales, Supply Chain, HR, and others across the organization and to gain the proper context from stakeholders.  In essence, Finance must maintain full access to critical information and meaningful participation from partners in the business.

As Finance transforms into the central hub within an organization, siloed and fragmented solutions are not sufficient for sophisticated organizations that are streamlining their budgeting, forecasting, and planning (see Figure 1).  After all, most organizations strive…

• To understand how internal and external forces impact performance management, Finance data must be integrated with data from different functions (e.g., Sales, Demand, Supply Chain, etc.).
• To enable better decision-making, agility and speed ensure the rolling forecasts get done in a timely manner, without compromising accuracy.
• For effective collaboration, the flexibility of a single unified platform is critical to unifying the forecasting function with data and processes across the organization.

Collaboration is forever joined to rolling forecasts, both fostering flexibility and enabling a response to economic pressures that traditional forecasts can’t.  Additionally, AI accelerates real-time data availability – allowing Finance, Operations, and Sales teams to regularly come together to assess the forecast makes for a more accurate and updated forecast.

Flexibility and Agility Required for Rolling Forecasts

We’ve previously defined a rolling forecast as “a management tool that enables organizations to continuously plan (i.e., forecast) over a set time horizon” vs. a calendar or fiscal year.  For example, in a 12-month forecast period, as each month ends, another month will be added.  In other words, forecasting involves always looking 12 months into the future (see Figure 2).

Best practice is to ensure rolling forecasts can extend (e.g., roll) beyond the current calendar or fiscal year-end.  Most commonly, rolling forecasts contain a minimum of 12 forecast periods, but can also include 18, 24, or more periods depending on the needs and complexity of the organization.

Rolling Forecast Strengthen Collaboration between Finance, Operations

In recent years, Finance leaders have taken on several major strategic initiatives to prepare for an ever-evolving landscape.  Replacing detailed annual planning cycles – which take too long and result in a budget that’s out of date as soon as it’s complete.  With continuous planning, however, Finance is more effective, focusing on rolling views that look 12 to 18 months ahead.  How?  Continuous plans enable managers to respond more rapidly to emerging events and trends and to changing business environments while increasing higher levels of corporate collaboration (see Figure 3).

Simply put, a rolling forecast is a call to action informing leadership of the need to engage and change when the forecast is updated.  Why?  Because rolling forecasts can transform the way Finance and Operations manage the business, obtaining better insights to make faster, more accurate decisions.  And at the end of the day, leaders know that highly engaged, collaborative employees create a healthier overall organization that will increase performance.

AI-Enabled Rolling Forecasting Enables Intelligence xP&A

Despite the rapid pace of adoption, many Finance leaders believe that FP&A teams must learn AI and machine learning (ML) modeling techniques when attempting to deploy AI-enabled rolling forecasts across the enterprise.  Further, for organizations with existing AI investments, FP&A teams generally lack the dedicated business analysts and data science engineers required to build ML models.  And as the adoption of AI and ML for rolling forecasts moves from fiction to fact, many FP&A teams are asking the same basic question:  Where to begin?

To start, don’t let AI market noise derail the evaluation process.  Here are 3 steps to consider in the process: 

• Start with a clear understanding of “what” business outcomes, your FP&A team is trying to achieve with AI and ML.
• Identify “who” is using the solution
• Consider “how” the solution is unified into existing planning processes.

Most AI solutions offer everything from AI infrastructure solutions to data science toolkits and complete AI platforms to create and deploy ML models.  While these are powerful tools addressing varying use cases, the tools aren’t designed for FP&A teams.

Conversely, purpose-built solutions like OneStream’s Sensible ML (see Figure 4) focus on a user-friendly, workflow-driven approach.  That approach allows Finance and Operations users to build, deploy and consume time-series ML models directly within a unified experience while accelerating productivity for existing data science resources.

And unlike “most” predictive forecasting solutions – which look at prior results and statistics and generate forecasts based on what happened in the past – Sensible ML has the capability to not only look at prior results but also then take on additional business intuition (e.g., events, pricing, competitive information, and weather) to help drive more precise/robust forecasting.

Those capabilities are exactly why a unified technology platform is so critical.  A unified platform instills confidence regarding information creation and gives organizations the flexibility to create operational relevance without compromising on control and governance.

Conclusion

AI-enhanced rolling forecasts can save huge amounts of work, freeing all managers and analysts to spend more time on value-added work.  Adopting these forecasts will also improve the relationship between Finance and Business managers.  After all, Finance will have more time to provide better service.

Learn More

To learn more about key considerations for the journey towards xP&A, click here to download the White Paper titled “Unify Connecting Planning or Face the Hidden Costs.”

Download the White Paper

Have you, as a financial analyst, ever sat in a meeting with Supply Chain, Engineering, Operations, and Manufacturing teams and felt like you needed a translator to follow what’s going on?  Many Financial Planning & Analysis (FP&A) professionals can relate.  They can understand the struggle of bringing together Supply Chain and Finance inputs to effectively forecast supply and demand as part of  Sales and Operations Planning (S&OP) processes.

In fact, the responsibility usually lands on FP&A to unify the demand plan with the financial plan.  But without cross-functional inputs from the Operations, Supply Chain, and Manufacturing functions, this responsibility can be a massive challenge.  However, the cross-functional inputs are an essential piece of the puzzle when elevating traditional FP&A software processes for eXtended Planning and Analysis (xP&A).

What Is S&OP?

Sales and Operations Planning is a process by which organizations forecast demand, supply, and financial plans to enable supply chain management.  While collaboration between the Operations and Finance functions has improved, there are still significant disconnects that result in a financial plan that doesn’t paint the complete picture of the enterprise.

Capturing these inputs within FP&A software does, however, give the whole picture.  The software helps align the organization by leveraging inputs beyond Finance that more effectively prepare the business to operate in turbulent market conditions.

How Does the S&OP Process Typically Work?

The S&OP process is typically run on a monthly cadence.  To start, the process involves data gathering and then moves through the demand and supply plans, plan reconciliation, and, finally, meetings and approvals (Figure 1).

Effectively leveraging the S&OP process to inform xP&A planning cycles gives an organization better insight into the plan beyond just the numbers.  In the xP&A process, leveraging these S&OP insights is important, and doing so in the most effective fashion is enabled by unifying the planning processes in a shared software environment.  Here are just a few examples of why unifying S&OP and xP&A processes are so critical to consider within FP&A software:

• When FP&A software is used for the S&OP and xP&A process, the analysis of data is faster and more accurate within the same software platform when compared to using multiple Excel spreadsheets or a siloed application environment.
• Data quality and accuracy are higher when planning is performed in one system, providing the most timely and accurate information to many users in the organization to support better collaboration.
• Comparing actuals to the forecast and plan is faster and more reliable when the data is available in one unified system, and forecasts are more quickly adjusted.

When FP&A isn’t part of the S&OP process, there’s often a disconnect between operational planning and the financial impact of the related decisions.  Balancing supply and demand impacts Finance as the balance influences revenues, cost of goods sold, profit margins, inventory carrying costs, headcount, cash flow, working capital, and various other financial metrics.

What happens when supply and demand aren’t balanced?  Well, when suppliers can’t deliver on time, it not only affects the organization’s ability to meet customer needs but also influences other non-financial metrics that are important to Finance.  Understanding these intricacies of the S&OP process can help Finance to develop a financial plan that takes these S&OP factors into account.  At the same time, Finance can lend insights into the process as it’s happening to ensure complete integration into the financial and operational plans (see Figure 2).

Incorporating the S&OP sales and demand planning outputs into the financial planning process provides, among others, two key benefits.  First, organizations can better understand the supply chain and operations impacts.  Second, organizations can also sense potential disruptions in supply chains and issues in manufacturing and labor availabilities.  These benefits are especially crucial in a post-pandemic new normal.  To remain competitive, FP&A must move away from a functional process and move to a business process that encourages collaboration and cross-functional integration of supply chain, sales, operational and financial data.

The new normal ultimately requires companies to be more agile and efficient than ever to react to real-time disruptions.  The ability to do so requires ensuring the insights and reporting gained from forecasting cycles are shared across the organization.  In turn, that capability enables the organization to better react to labor shortages and fluctuations in the availability of raw materials and resources that would otherwise slow or stop production amid high demand.

Key S&OP Metrics for FP&A

The S&OP process has both financial metrics as well as demand and supply metrics, and the financial metrics are important to incorporate into the financial planning process.  Here are some of those key financial metrics:

• Total Sales: Since S&OP deals with demand and supply forecasts, total sales data will help assess the financial health of the organization.
• Gross Margin: The goal is to have total sales meet projected targets, but just as important is ensuring that the gross margin is meeting projections.
• Working Capital Projections: It’s essential to check that the organization has as much working capital available as the team forecasted.  If the number falls short, it might be time to evaluate why and adjust projections.

Why Effective xP&A Must Unify FP&A & S&OP

During the S&OP process, the financial implications of the decisions are vital considerations, but the exclusion of Finance means these decisions are often overlooked.  Ensuring that the financial perspective is considered during the development of the demand and supply plans lends weight to the decision-making happening as part of the S&OP process.

Conversely, if Finance is preparing the demand plan as part of the FP&A process without Supply Chain buy-in, there will be frustration from both groups.  Why?  Because they’ll be operating on different assumptions and understandings of the organizational objectives.

Conclusion

Ultimately, FP&A is not only a key input to the S&OP process but also a consumer of the output.  It’s just as important for Finance to be involved in the process as it is for the output to inform the FP&A, and now xP&A, planning cycles.  Understanding the financial implications of the demand and supply plans developed as part of the S&OP process helps align organizational goals – from both a Finance and Supply Chain perspective.

Learn More

To learn more about how your organization can grow your FP&A process to xP&A, click here to watch a video on the 5 Key Factors to Consider in the FP&A Evolution to xP&A.

Watch the Video

All CFOs and Finance leaders know an important truth: all data ultimately leads back to the income statement, balance sheet, and cash flow.  With that in mind, eXtended Planning and Analysis (xP&A) takes traditional financial planning and analysis (FP&A) and changes the game.  How?  By unifying plans and forecast data from across the enterprise.  That allows Finance to synchronize operational plans and forecasts into a single, unified plan that can inform business decisions for all departments.

And for FP&A teams, storytelling – the ability to combine financial and operational data and tell a story that reflects business performance and/or risks – is a vital skill.  That’s been especially true during the COVID-19 pandemic and the disruptions it has caused.  Amid the related uncertainty, organizations have been stretched thin, asked to do more with less, and expected to react quickly to unpredictable disruptions in global supply chains.

Finance professionals understand these pressures all too well.  Why?  Well, with so much reliance on spreadsheets and legacy corporate performance management (CPM) applications, it’s often Finance that feels the pain of combining large, disjointed datasets from disparate systems and manually consolidating data.

But what if organizations could replace spreadsheets and disparate silos of data with a unified data store and visualization environment that can be quickly and reliably refreshed?  One that not only ensures data quality but also brings the data into an easily consumable reporting and analytics platform.  One that enables the storyteller to drive key decisions quickly and easily across xP&A processes.  All of that and more is possible through storytelling that drives effective xP&A.

Use Storytelling to Drive Effective xP&A

Today, storytelling capability isn’t just nice to have.  It’s an absolute necessity if you want to operate effectively amid seemingly endless economic uncertainty.

Here are some of the key benefits of leveraging visualizations for storytelling to drive effective xP&A:

• Keeps data accessible to an audience that includes functions outside of Finance.  Visualizations help the storyteller translate complex financial data into a digestible and quickly understood format that can be delivered to managers in various functions – even those less accustomed to reading financial reports.
• Makes data consumable to leadership that needs rapid insights.  The pace of business is increasing, and busy professionals must be able to easily and reliably understand and react to rapidly changing data.  Sifting through mountains of spreadsheets and reports, however, does not enable keeping with the pace of modern business.  Visualizations can help users identify trends and signals in a large, complex dataset and ensure the audience can understand the key takeaways more effectively.
• Supports dynamic data sets that can be updated and refreshed quickly to enable swift action.  Interactive dashboards can ingest near real-time data and be updated on the fly.  This capability can transform a monthly forecasting cycle into a more dynamic process to help organizations understand and react to change instead of wondering why something happened after the fact.

Enable Easier Access to Data Using Visualizations

It’s said that a picture is worth a thousand words, and as many financial analysts can attest, painting the proper picture with visualizations (see Figure 1) is critical when telling the story behind a large dataset.  When taking FP&A to the next level by shifting to an xP&A process, organization-wide collaboration drives the unification of financial and operational plans across the enterprise.  Combining data from various sources into interactive dashboards with precise visualizations (see Figure 2) makes the data accessible to a wider audience and enables the alignment of operational plans with organizational goals.

Why is that so important?  Well, utilizing these dashboards and visualizations can enable Finance professionals and leadership to make more informed and rapid business decisions.  Those decisions are enabled by everyone staying informed of changes in financial performance with easily refreshed, quickly consumed representations of the data.

Ensure Data is Consumable Using Visualizations

Sharing consumable data with the audience is crucial to storytelling.  Why?  Because time is valuable and in short supply these days.  And if key stakeholders cannot quickly assess risks and opportunities to drive performance without needing hours to sift through reports and spreadsheets, then FP&A has failed.

In the age of disruption and volatility, it’s more important than ever that organizations can consume and react quickly to whatever the data is saying.  And they can do it in real-time to predict what’s coming next, which is critical given the uncertainty and instability caused by the pandemic and other global disruptions.  Utilizing quickly and easily refreshed data visualizations ultimately helps leaders gain insights critical to keeping organizations running as smoothly as possible.

Ensure Data is Dynamic Using Visualizations

Having dynamic data at your fingertips is crucial to being able to quickly detect and react to change.  Yet many Finance leaders have experienced the pain of being reactive instead of proactive to issues that arise with the financial plan.  Instead, leveraging reliable and easily refreshed dashboards that offer near-real-time visual insights into the trends and financial signals the data is revealing can enable organizations to respond more quickly and more reliably to anomalies.  That’s why dynamic visualizations are so critical.

Here are just a few examples of the key benefits for xP&A:

• Regularly refresh data to provide daily or weekly financial signals that drive operational performance and action prior to month-end.
• Combine and align data from Sales, Operations, Finance, and other KPIs into a single visualization to enable actionable insights and collaboration.
• Proactively react to variances and quickly inform downstream customer, product, purchasing, and staffing forecasts.

Conclusion

For most organizations, dashboards and visualizations are not new, but leveraging them for xP&A is especially important to remain competitive and agile in the face of unprecedented global disruptions. Being able to quickly and reliably refresh and access data and bring it together in a way that can be shared across the organization is crucial – and telling that story through visualizations is a powerful tool in the Finance toolkit.

Learn More

To learn more about using OneStream to create data visualizations for xP&A, download our reporting and analysis e-book here.

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OneStream recently released version 6.8 of our platform, designed to drive speed and flexibility for financial and operational planning and reporting.  This release is all about improving the user experience for our customers, from enhanced ease-of-use capabilities with new chart types to an enriched Financial Class Functions experience.  Additionally, OneStream 6.8 features a powerful new capability called Drill to Dashboard.

Read on to learn more about these capabilities and how they can help organizations like yours plan and report with more speed and flexibility than ever.

Supporting eXtended Planning & Analysis (xP&A)

OK, let’s cut to the chase with the most powerful new feature in the 6.8 release.  Drill to Dashboard is part of the broader effort to further improve the OneStream user experience for eXtended Planning & Analysis (xP&A) use cases.

Here are a few of the core requirements driving our newest innovations:

• Corporate performance management (CPM) applications inevitably evolve to keep pace with the growing need for enhanced planning and Finance storytelling.  That growing demand for enhanced planning and storytelling leads to more granularity and a continued need for scalability and performance for planning and reporting on larger volumes of more detailed data.
• As organizations optimize and enhance their applications, the natural evolution can drive the need for easier access to reference data from dashboards, such as linked Cube Views to access more detailed data in BI-Blend tables or the relational register.

To address those realities, Drill to Dashboard now opens the door to many possibilities for data lineage analysis and data exploration.  This added functionality will help to eliminate the need for users to incorporate too much detail in a single Cube View and/or Dashboard.  Instead, users can now “navigate or drill-to” the details as needed (see Figure 1).

If you’ve ever felt the challenges of tracking down specific data for management reporting, you know the pain of jumping from one report or dashboard to another. Or realizing you think you know what data the Dashboard or Cube View contains only, to find out you were wrong. Sometimes a seemingly simple request can take hours, if not days to fulfill due to data not easily being accessible.

Drill to Dashboard enables users to quickly and seamlessly obtain the slices of data required for planning or reporting – and do it at speed.

For example, with Drill to Dashboard, users can quickly pass parameters from a Cube View to Dashboard for fast, focused reporting and analysis.  Users can also link multiple Dashboards and link Dashboards at different levels, leveraging the entire Cube View or specific Cube View Rows or Columns for planning or forecasting.

In other words, Finance teams and business analysts can continue to focus on delivering the data needed to drive enhanced reporting, informed decision making, and improved business performance.

Below is a quick summary of additional features available in OneStream 6.8 and the benefits to all customers.

New Financial Class Functions

Users can do more calculations with the Microsoft Financial Class suite of functions.  Now available in the Business Rules Editor, users can take advantage of the class procedures that perform financial calculations, such as depreciation, present, and future values, interest rates, rates of return, and payments.

Ease-of-Use Features

The New Chart Types in the Spreadsheet within the OneStream Windows App offers powerful features in the OneStream platform that enable users to transform data into better insights by quickly visualizing common financial, statistical, and hierarchical data.  In OneStream 6.8, we introduced seven powerful charts providing users the ability to explore data and tell richer stories.

Here are the new chart types and the benefits users can expect:

Waterfall chart quickly illustrates the line items in financial statements and gives users a clear picture of how each item is impacting the bottom line.  The Waterfall chart is a great way for users to get a complete picture of how different factors combine to achieve the “final result.” Comparing product earnings, showing budget changes over time, or illustrating employee growth are all good examples of ways users can benefit from a Waterfall chart (see Figure 2).

Sunburst chart lets users easily see the largest contributing segments within a hierarchy of multiple levels.  The Sunburst chart shows hierarchical data and their proportions, but it can also show more levels and how a ring is broken into contributing pieces.  For example, through the Sunburst chart, users can better understand revenue sources of your business or salary expenses of employees across departments (see Figure 3).

Treemap chart provides a hierarchical view of user data and an easy way to compare different levels of categorization.  Treemap charts are great for highlighting the contribution of each item to the whole, within a hierarchy. Making it easier than ever to spot patterns or compare proportions and relative sizes.  Representing balance sheets in a Treemap chart, for example, offers very quick insights on how the company is financed (such as debt rather than equity) or where the largest portion of assets lies (see Figure 4).

Other new chart types introduced in OneStream 6.8 include the following:

• Box and Whisker plot provides users with key insights about the distribution of data from different categories. Including range, quartiles, mean, and outliers.
• Histogram chart helps users analyze the characteristics of a large amount of numeric data, through a graphical representation of its distribution.
• Pareto chart lets users sort the frequency of the most prevalent issues (the bar graph). Then shows the additive contributions of each issue as users move along the horizontal axis (the line graph).
• Funnel chart lets users visualize the progressive reduction of data as it passes from one phase to another.

Learn More

If you’re an existing customer looking to learn more, check out the OneStream 6.8 release notes on the OneStream MarketPlace.  Not yet a customer?  Sign up for our upcoming webinar or another upcoming event.

As your FP&A team begins the xP&A journey, download our whitepaper to learn more about the key factors that are critical for effective xP&A.

Download the White Paper

While many of our customers are busy prepping 2022 budgets, at OneStream, we recently delivered our latest quarterly platform release, boosting your corporate performance management capabilities.

For both new and existing customers, OneStream version 6.6 is a must-have. We’ve enhanced the ease of use with Task Scheduler, added new Waterfall Charting capabilities, and enriched the Excel Add-in and native Spreadsheet experience. Plus, OneStream 6.6 also includes a powerful new capability called Hybrid Scenarios. Read on to learn more about these capabilities and how they can help organizations plan and report with more speed and flexibility.

Supporting eXtended Planning & Analysis (xP&A)

OK, let’s cut to the chase with the most powerful new feature in OneStream’s unified Intelligent Finance Platform. Hybrid Scenarios are part of a broader effort to further improve the OneStream user experience and eXtended Planning & Analysis (xP&A) use cases. How? By providing agile and flexible features to help organizations like yours lead at speed.

A few core realities are driving our newest innovations.

First, corporate performance management (CPM) applications inevitably grow and evolve over time through several different levers but primarily through the addition of more dimensions and additional dimension members. That growing dimensionality leads to higher data volumes and a continued need for scalability and performance for planning and reporting on larger volumes of more detailed data.

Second, as companies optimize and enhance their applications, the natural evolution can drive the need for model changes, such as splitting up cubes to focus on slices of a dimension and data sets. Unfortunately, splitting cubes traditionally comes with extra costs for data movement, data synchronization, and additional overhead management.

Now with OneStream, Hybrid Scenarios allow the application to easily grow with an increased demand for dimensions and any additional growth of members within dimensions, giving users the ability to choose the right capability for your specific needs. (See Figure 1)

If you’ve ever felt the pressure of tracking down specific data for management reporting, you know the pain of not having it. Or realizing you have it only to find out it takes a painfully long time to gather and format. Sometimes a seemingly simple request can take hours, if not days to fulfill due to data complexity and volume.

Leveraging Hybrid Scenarios helps end that pain. With this new capability, users can quickly and seamlessly attain the slices of required data for planning or reporting—and do it at speed.

For example, with Hybrid Scenarios, users can quickly “share data” from an existing source scenario for fast, focused reporting and analysis. Users can also “copy data” from a source scenario and seed a new scenario for planning or forecasting.

In other words, whether you’re on the Finance team or a business analyst, you can focus on delivering the data needed to drive informed decisions and improve business performance.

Below is a quick summary of additional features available in OneStream 6.6.0 and the benefits to customers.

Ease-of-Use Features

Task Scheduler: This is a powerful feature of the OneStream platform that enables users to automate the running of data integration and data management processes. In OneStream 6.6 we introduced new settings in the Task Scheduler providing users the ability to set the Minutes (Hourly) schedule with more granularity around the time in which the tasks are executed (See Figure 2). This includes:

• Schedule recurring tasks in minutes during a defined block of time (run window) each day
• Execute tasks in a limited timeframe at a certain time of day/eve to enhance resources control (e.g., run my task every 60 minutes: between 8pm and 11pm)

Waterfall Chart: This significant new chart type adds to the already robust Dashboard options currently available. In OneStream 6.6 we introduced Waterfall Chart interactive capabilities with some additional new series settings that enhance data visualization capabilities. (See Figure 3).  This includes:

• Intuitive and easier-to-use functionality when assigning colors to the series (e.g., Start Bar Color, Total Bar Color, Rising Bar Color, Falling Bar Color)
• Variance value display for each bar
• Total included in series (i.e., Total Value Label)
• Positive (top of bar)/negative (below the bar) variance label positioning

Excel Add-In/Spreadsheet: Finance users heavily leverage OneStream’s Excel Add-in and native Spreadsheet feature for data entry, reporting, and analysis while letting our platform provide control and governance on the back-end.  OneStream 6.6 adds the ability to use VBA (Excel Macros) when using large Excel files with multiple tabs to automate the files to set data rather than opening up each file one by one and using the Submit function in the Excel Add-In.  The XFGETCELL, and now XFSETCELL, functionality can be surfaced using VBA to run a macro to set and get data via VBA.

• Includes Excel VBA Submit Data function (SubmitSetXFFunctions), a new VBA XFfunction that provides the ability for Excel Add-In users to submit data via XFSETCELL via an Excel Macro (or VBA)
• Enhances ability to automate submitting data back to OneStream database when used with XFSETCELL

Advanced Design & Analytical Features

BI Viewer Dimension Hierarchy Support.  This new feature in the OneStream BI Viewer enables viewing data in an easy-to-understand hierarchical format via dimension leveling. With the BI Viewer, users can design various dashboard items (e.g., grids, pivot tables, charts, etc.) in which to view the dimension-leveled data. (See Figure 4). New features include:

• New “Dimension Level” property in Cube View MD
• Option to create levels sourced from a Cube View
• Columnar format in BI Viewer to build hierarchical presentations
• Visibility into functional hierarchies in BI Viewer
• Ability to drill into lower-level tree items

Imagine, your users walking into the office knowing they will no longer be bound to rigid views of hierarchies in your legacy finance reporting tool. Sounds great, doesn’t it? This powerful new OneStream feature within BI Viewer specifically addresses the challenges users may have felt in the past. The feature will also enrich the reporting experience through increased flexibility that increases efficiency.

Learn More

If you’re an existing customer looking to learn more, check out the OneStream 6.6 release notes on the OneStream MarketPlace.  Not yet a customer?  Sign up for our upcoming webinar or another upcoming event.

As your FP&A team begins your xP&A journey, download our whitepaper to learn more about the key factors that are critical for effective xP&A.

Do you know if your organization is using the best budgeting and forecasting process possible? Tried-and-true static budget methods are what many organizations resort to today. But static budgets built within legacy financial forecasting software are not flexible enough to react to what’s happening in the business during the budget period. Meanwhile, rolling forecasts are designed to change and adapt throughout the year, which provide more value if large and sudden changes impact your business. Now is the time to take the best of modern finance planning and extend it across the enterprise through xP&A (extended planning and analysis). Read on to learn more.

Let’s face it, the world is changing rapidly, and organizations face tremendous pressure to evolve with the changes. It’s no longer good enough for Finance and Line of Business leaders to create an annual plan with financial forecasting software and make multiple adjustments throughout the year.  Why?  Well, as the pace of change increases, annual plans become increasingly less relevant and, in many cases, are completely abandoned by Finance chiefs before the ink even dries.

As Finance transforms into the central hub within an organization, static budgets alone are not sufficient for budgeting, forecasting, and planning.  It isn’t that the annual budgeting process isn’t a useful exercise.  After all, the process still…

• Plays a key role in transforming business plans into financial goals.
• Remains critical for demonstrating what resources must be deployed and when to make the strategic vision a reality.
• Helps track how actual performance compares to the strategic financial plan.

But static budgets do little to help organizations drive ongoing performance.  Why?  Well, annual plans are generally reactive to changing conditions.  Such plans are also time-consuming to build and update, inflexible and ineffectively utilized – causing employees to lose faith in the budgeting process.  The budgeting, planning, and forecasting process is seen as an exercise imposed by Finance and yielding little benefit to operational groups (e.g., Sales, Marketing, Supply Chain).

Albert Einstein perfectly captured why static budgets need to go: “Insanity is doing the same thing over and over and expecting different results.”

Today, Finance chiefs are challenged with helping their organizations break the reliance on annual plans and embracing more agile planning techniques including driver-based planning and rolling forecasts.

Optimizing Day-to-Day Performance

Rolling forecasts (see figure 1) are extremely beneficial for large and dynamic enterprises as financial forecasting software tools to help continually adapt planning processes to actual performance and market trends.  How?  Rolling forecasts allow for more accurate and multifaceted forecasting by re-calibrating the forecast based on changes in both internal variables (e.g., changing demand volume and pricing), and external factors (e.g., fluctuations in the industry, economy, weather, or geopolitical ecosystem).

Below are a few additional reasons annual plans do little to help manage day-to-day performance:

• Valuable time for managing the organization is squandered on chasing “what happened.”  For instance, your April forecast for the rest of the year is already projecting too many variances and will no longer support your well-reasoned annual plan. At this point, most organizations start scrambling to get the forecast “good enough” without knowing what caused the variances that impacted the annual plan.  The result is time spent making current numbers fit a stagnant plan rather than making decisions to support organizational strategy and growth.
• Too little attention on moving the strategic needle due to reactively reconciling data against the annual plan.  What happens when management asks why certain line items are abnormally high compared to last year?  A reactionary response.  Rather than focusing on forward-looking insights, you spend the next week chasing down data from multiple systems, merging and validating the data, and finally, reconciling the data to support management reporting.  Strategically, nothing gets accomplished, but far too often, organizations find themselves in these reactionary situations.
• Activities to support the plan focus on discussions rather than produce real decisions.  Remember when you could establish an annual plan, adhere to it all year and make meaningful adjustments based on forward-thinking decisions?  Unfortunately, this idealistic concept is allusive to most organizations.  Why?  Well, variables like the weather impacting supply chains or downturns in industry-specific demand can kill even the most well-reasoned annual plan on day one.  The challenge lies in having a process flexible enough for the onslaught of variables while dealing with an inherently rigid annual plan.  A rolling forecast is flexible by nature and can account for organizational challenges – allowing you to produce true insights to make real decisions.

We’ve previously defined a rolling forecast as “a management tool that enables organizations to continuously plan (i.e., forecast) over a set time horizon” vs. a calendar or fiscal year.  For example, in a 12-month forecast period, as each month ends, another month will be added.  In other words, you’re always forecasting 12 months into the future.

Best practice is to ensure rolling forecasts can extend (e.g., roll) beyond the current calendar or fiscal year-end.  Most commonly, rolling forecasts contain a minimum of 12 forecast periods but can also include 18, 24 or more periods depending on the needs and complexity of the organization.

Here’s a summary on the key differences between traditional and rolling forecasts (see Figure 2):

Keep It Simple to Best Solve a Complex Problem

Simplifying how your team approaches forecasting is a keyway to drive efficiency, which is a key driver of value.

Luckily, we previously provided a framework to get you started on the first steps to becoming an agile Finance organization.  But there’s an additional accelerator to consider, supercharging accuracy and delivery, with the concept of eXtended Planning and Analysis (xP&A).

The paradigm shift from traditional FP&A to xP&A (see figure 3) offers a way to fully support a rolling forecast by enabling the inclusion of all organizational functions into a cohesive unified process and platform that adjusts to challenges and needs.

According to Gartner [1], by 2024, FP&A is expected to encompass xP&A, a strategy where “x” denotes how the traditional silos separating enterprise financial and operation planning processes are broken down.  The result?  A new level of transformative business value.

At OneStream, we call this Intelligent Finance.

Learn More

As your FP&A team begins your Rolling Forecast journey towards organizational agility, download BARC’s (Business Application Research Center) latest Future of Planning survey here to learn more and contact OneStream if your organization is ready to make the leap from static planning to agile forecasting

_{[1] Magic Quadrant for Cloud Financial Planning and Analysis Solutions, Greg Leiter, Robert Anderson, John Van Decker, 6 October 2020}