As modern Finance leaders navigate the turbulent global landscape, the path ahead for Financial Planning & Analysis (FP&A) gets clearer every day. A pivotal shift is occurring, emphasizing the need to unify connected planning to foster alignment between Strategy, Finance and Operations. Not too long ago, however, the ambitious vision of integrating financial and operational planning into a seamless ecosystem faced setbacks due to technological limitations. The rapid advancements in planning processes outpaced the supporting technology – a predicament many businesses might recognize.
But here’s the truth: organizations now stand at a crossroads – embrace unified connected planning or risk incurring hidden costs.
Despite technological advances and increased data accessibility, Finance is still struggling to synthesize all planning across the enterprise into one cohesive and ongoing process. In fact, according to a 2023 report from the American Productivity and Quality Center (APQC), only 26% of CFOs surveyed say their respective company’s approach to annual budgeting is valuable. Plus, even the CFOs themselves admit that improvements are needed
Today’s Finance leaders must maintain board, investor and stakeholder confidence while providing actionable insight to line-of-business managers. To do so, CFOs and Finance managers must, now more than ever, deliver fast, accurate and valuable financial and operational information that can be trusted.
Finance leaders can now leverage modern technology to rid themselves of legacy systems and processes while embracing future trends prevalent in today’s market.
Spurred by technological advances, the speed of analytical disruption in organizations is already perpetually fast – and only getting faster. As Finance groups prepare for the transformation ahead, 3 key trends are reshaping the future of how organizations will generate value from reporting and analytics initiatives:
As Finance teams respond to a rapidly changing business environment, FP&A is extending its reach to include and collaborate with Sales, Marketing, Supply Chain, Talent Management and IT to accelerate enterprise agility. This unifying framework – known as eXtended Planning and Analysis (xP&A) – enables continuous collaboration and performance management by using a single, composable platform and architecture.
Financial analysts and decision-makers are drowning in complex data. To better process that data, organizations are increasingly enhancing traditional dashboards with dynamic data-driven insights powered by artificial intelligence (AI) and machine learning (ML). The resulting dynamic data stories generate insights as narratives, highlighting the most meaningful changes in the business for each user – with root causes, predictions and prescriptions for the roles and contexts. In turn, the enhanced data-driven insights reduce the risk that financial and operational analyses will be misinterpreted.
The way Finance teams manage the data behind dashboards and visualizations is changing. How? Finance can use modern technologies to deploy a host of new models and tools to provide actionable financial and operational data that drive effective decision-making. More specifically, technologies such as ML and AI are leveraged to automate various tasks required during the analytics process – and to discover, visualize and narrate important findings in vast data sets. AI and ML ultimately enable Finance to reduce the time it takes to perform the day-to-day input- and output-focused activities that consume analysts’ time – without requiring the full-time support of data scientists. (See Figure #1)
As organizations navigate the ever-evolving landscape, staying ahead of the curve is paramount to success. While the adoption of modern technologies and embracing key trends can bolster an organization’s financial agility, there comes a crucial juncture when scaling connected planning becomes imperative. Recognizing the signs that indicate the right time for this strategic move can make all the difference in propelling a company towards its goals and sustaining growth.
The continuous sophistication of organizations makes it challenging to harness technology to bolster Finance. When those challenges are coupled with the pressures of volatile revenue streams, Finance leaders are tasked with managing growth, optimizing emerging technologies, addressing globalization demands, evolving target operating models and empowering mobile employees. These leaders must also explore innovative avenues to boost productivity, optimize costs and maximize the value of relationships.
If your organization is evaluating whether it’s ready for Finance Transformation, here are 5 key signs it’s time to scale connected planning.
One clear indicator that it’s time to scale your connected planning efforts is when your organization experiences a significant increase in complexity and data volume. As the business grows, you’ll likely encounter more intricate planning challenges that cannot be effectively addressed with traditional planning methods. Instead, scaling your connected planning capabilities will allow you to leverage advanced analytics and data integration to handle complex planning scenarios, accommodate large data sets and gain deeper insights into business operations.
Disconnected FP&A planning processes often result in silos, leading to a lack of coordination and collaboration between different departments. If you notice your teams are struggling to work together, duplicate efforts or encounter difficulties aligning plans, those signs are a clear indication you need to scale your connected planning efforts. By implementing an integrated planning solution, you can break down departmental barriers, encourage cross-functional collaboration and ensure everyone is working toward a shared set of goals.
Are planning cycles taking longer than necessary, causing delays in decision-making and hampering your ability to respond swiftly to market changes? If so, those signals are telling you the time is now to scale your connected planning efforts. Automating and streamlining your planning processes through connected planning will reduce manual work, eliminate redundant tasks and significantly speed up your planning cycles. In turn, this increased efficiency allows you to make informed decisions faster and stay ahead of the competition.
If your FP&A organization is consistently struggling with inaccurate forecasts or failing to meet performance targets, your planning processes may be falling short. (See Figure #2) Scaling connected planning can help you improve forecast accuracy by leveraging real-time data and advanced forecasting models. With access to up-to-date information and robust predictive capabilities, you can make more reliable projections, identify potential risks and opportunities, and take proactive measures to achieve better performance outcomes.
As your business expands and evolves, you need planning processes that can scale and adapt accordingly. Traditional FP&A planning methods often lack the flexibility to accommodate growth or respond effectively to market shifts. scaling connected planning enables you to handle increased demand, seamlessly integrate new business units or acquisitions, and adjust your plans to align with evolving market dynamics. Scaling therefore provides the scalability and adaptability needed to support your organization’s long-term growth strategy.
Connected planning is a powerful approach that can revolutionize how your organization manages its planning processes. Recognizing the signs that it’s time to scale your connected planning efforts is crucial for staying competitive in today’s fast-paced business environment. And by addressing increasing complexity, fostering collaboration, improving efficiency, enhancing forecast accuracy and enabling scalability, you can unlock the full potential of connected planning and propel your organization toward greater success. Embrace the opportunity to scale connected planning, and watch your business thrive in the face of changing landscapes.
To learn more about how organizations are scaling connected planning, click here to read our whitepaper on the topic. And if you’re ready to take the leap from spreadsheets or legacy CPM solutions and start your Finance Transformation, let’s chat!
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Strategic workforce planning is crucial for business leaders today. Why? Because the labor market is facing unparalleled forces of change: demographic upheaval, talent scarcity, evolving employee preferences when choosing an employer, and the ubiquitous and growing presence of artificial intelligence.
Running strategic workforce planning together with Finance in one unified solution is a best practice that ensures people plans align with strategic and financial objectives.
In fact, unifying workforce planning with both strategic and financial planning sets up organizations to thrive under unsettled market dynamics.
Before effectively implementing strategic workforce planning, an organization needs to understand what it entails, why it’s so unique, and how Enterprise Performance Management (EPM) adds value to such planning. But where to start?
Strategic workforce planning is a long-term planning approach to hiring the right people (not just about a set of skills and expertise) at the right time (to match the business needs) and in the right place. This effort should also be fully aligned to the strategic goals of the organization. A strategic workforce planning model is pictured in Figure 1.
In simple terms, an organization needs to manage the following 3 factors to meet strategic objectives:
Cash is like the “wild card” in that it grants access to people and assets.
Assets are somewhat certain. For example, an organization can classify an “office building” by a set of common characteristics within any office building (e.g., square meters, location, open spaces, power, and HVAC equipment, etc.). And that’s it — the requirements when searching for an office space somewhat match easily with the characteristics of available space.
However, people can’t be tagged in a similar way. For example, an individual may prefer higher compensation versus better work-life balance. And at a later stage in life, that same individual may prefer the opposite. Some people also value the work environment and team spirit more than others. In essence, every person is a unique individual, so planning for people requires certain solid patterns to do it right. An employer may have well-defined requirements for a job type, but each candidate will respond differently to the compensation and benefits package available.
This uniqueness makes planning and managing the workforce a difficult job for recruiters and HR departments. In addition, day-to-day operations and challenges may divert the attention of HR leaders, who could then lose sight of the strategic goals of the company. Here’s where an EPM solution for people planning can help.
Finance teams can connect business strategy with HR planning. Why? Well, besides looking after the financial health of the company, Finance teams support leadership in shaping the strategy. They also have access to the best technology for strategic planning. Modern EPM solutions combine planning, consolidation and reporting capabilities all in a single solution. This includes a unified data model hosted in one platform that can also manage strategic workforce planning under the xP&A construct (Figure 2).
HR leaders should therefore partner with Finance teams when building the strategic workforce plan and use the same technology. Below are 6 ways a unified EPM solution can support strategic workforce planning:
Today, strategic workforce planning is crucial amid uncertain market conditions. Yet strategic workforce planning shouldn’t be done alone. Why? Because it must lean on Finance teams to connect with strategy. Otherwise, organizations are left with just workforce planning, without the “strategic” piece.
An extensible EPM solution supports people planning and the financial model under the same data model– bringing significant advantages and business benefits to the table.
Bunge – a global leader in agribusiness, food and ingredients – uses the OneStream Intelligent Finance Platform to align people planning with strategy and performance. Want to hear more about how Bunge manages that alignment? Watch the webinar recording:
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Changing rooted behaviors is one of the hardest jobs for leaders. And what about trying to bring innovative technologies and novel approaches to accomplishing tasks tied to those rooted behaviors? Well, that’s a lot like pulling teeth. But those changes pay off, for they position the organization to reach higher levels of value.
This blog post introduces machine learning for demand planning by looking at how car safety relates to demand planning, and exploring the obstacles organizations might experience with adoption and how to overcome them.
When thinking about car safety, most people likely picture one or more of the images below:
Volvo first comes to mind first. And indeed, Volvo pushed for standardizing the 3-point seatbelt in the car industry, so the company can proudly take credit for saving millions of lives  since the 1970s. But adoption didn’t come easily. Why not? Well, it’s simple. Safety belts meant a radical change in people’s habits with a difficult trade off: losing comfort for safety in the supposed event of an unlikely accident . Using safety belts meant a behavioral paradigm shift for drivers and passengers alike that even today faces resistance from some motorists. And to make true change possible across the industry, Volvo had to open up the patent for safety belts to competitors to accelerate adoption.
Similarly, just like drivers and passengers with the introduction of the seat belt, demand planners are going through a behavioral paradigm shift with the introduction of machine learning (ML). Why? Because old habits die hard! Let’s dive into it.
Demand planning work is usually a manual activity grounded in a low-accuracy system-generated baseline. To get the accuracy right, several external and internal source inputs enrich and adjust this baseline multiple times. Spreadsheet wrangling, reconciliation and error are thus inevitable fallouts of this approach. Yet many planners prefer it. Why? Because they feel comfortable with it. That also means they refrain from learning new technologies and methods despite – as is the case with ML – the game-changing benefits. Using machine learning for demand planning drastically improves accuracy and exponentially increases the number of forecasts run.
Fortunately, not every organization is resistant to changing the status quo. Some companies are trailblazing the adoption of machine learning to improve forecasting accuracy in demand planning. One such company is Autoliv, a tier-1 automotive supplier of safety components for major carmakers in the world.
Supplier relationships in the automotive industry are based on a pull system that gives car manufacturers strong leverage on pricing. Consequently, margins can be razor thin for suppliers, and the risk of falling into loss is high. This axiom is valid in other industries as well, including in transportation, retail, wholesale, consumer products, and more.
While margins can be improved in many ways, a robust approach is needed to better understand and plan demand effectively. Why? Because an organization that appreciates the business drivers that shape future demand can better draw sales projections. Additionally, the organization can better adjust inventory levels, avoiding stock outs and breaches of service levels.
Autoliv offers a good real-world example of putting this robust approach in action. How? The company successfully embarked on a transformation journey to have a single view of profitability across Sales, the Value Chain and Finance. Autoliv also knows that – in the automotive industry – understanding demand is key to protecting and growing profit margins. Accordingly, the company is exploring the use of Sensible Machine Learning to improve demand planning. You can read the Autoliv case study here.
Many organizations are using artificial intelligence (AI) or machine learning (ML) in the business in one way or another. One of the most used approaches is to build a data lake and apply ML algorithms. However, this approach does not always work well for planning use cases. When dealing with ML for demand planning, organizations may encounter the following challenges that hinder adoption:
Not to mention, resistance to change can be high, and only 13% of standard ML projects make it into production. What’s the point of producing an ML forecast that no one uses?  Luckily, there is a way to deal with the obstacles along the way.
Having the expected benefits clear from the start is key when considering machine learning for demand planning. Does it need to underline new patterns? Should it address variability? Can it produce a high volume of forecasts at speed? The ultimate litmus test is that the solution delivers more forecasting accuracy and that planners are trusting it.
Many organizations hold a vast amount of data, but it is pocketed in different systems and databases. When a lot of effort goes into preparing the data for the ML engine, organizations may lose sight on what’s important. A solution that can ingest volume and disparate datasets is therefore key for demand planning use cases. For that reason, the following key attributes must be considered when looking for an ML solution for demand planning:
Beyond considering the necessity of the above attributes, organizations must also stay focused on the business outcomes they expect.
When an organization has clarity on business outcomes, ML and other technologies become an enabler to accomplishing those outcomes. This clarity on goals helps organizations decide between costly and lengthy home-built ML solutions and market-leading planning solutions with built-in ML services. The latter will help better break old habits, enable enterprise-wide adoption and accelerate the time to value.
Ready to find out how to break away from old habits on demand planning?
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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.
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.
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:
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.
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.” 
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:
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.
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.
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:
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.
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.
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 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:
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.
Unified business planning is anchored on 3 key principles:
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.
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.
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:
Learn how to maximize the benefits of Integrated Business Planning in our next blog:
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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.
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:
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.
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?
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 how to unify Integrated Business Planning in our next blog:
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