QueBIT Blog: xP&A Data Hub Primer for the CFO

Posted by: Ann-Grete Tan

Jun 1, 2021 9:22:00 AM

Until as recently as 2018, the term xP&A (eXtended Planning & Analysis) didn't exist. It was coined in 2019 by Gartner to visualize the evolution of Financial Planning and Analysis (FP&A). It was typical of the finance team, before 2019, to work in a silo - they alone were responsible for all the data, intelligence, and financial planning requirements of the company. But xP&A aims to extend these planning and analysis capabilities beyond the boundaries of the finance domain and into other operational areas of the enterprise such as sales, supply chain, and HR. In a way, xP&A represents the convergence of traditional FP&A with integrated business planning (IBP).CFO-Blog

By connecting all these departments, xP&A allows businesses to integrate forecasts and metrics from across the organization into one consolidated plan. Not only does this make the organization's decision-making ability more agile, but it also increases visibility into the interdependencies of each department, allowing executives to identify problem areas and target new growth opportunities. Moreover, it frees the firm from the crippling limitations of spreadsheets and enables them to harness data and explore potential opportunities with Artificial Intelligence (AI) and Machine Learning (ML).


Unfortunately, many firms struggle to achieve all the benefits promised by xP&A and fail to garner the results that had been expected. This failure isn't due to the shortcomings of xP&A but because of the inability of firms' to create the conditions for success. To navigate xP&A successfully, firms need to undertake three steps -

  1. Investing in a planning software platform that supports driver-based and predictive modeling powered by AI and ML.
  2. Committing to business process change - internal as well as external.
  3. Data gathering and reporting.

The first step is often the easiest step for organizations. By investing in new software, they hope to resolve their planning and analytics issues quickly. In the short term, this might seem sufficient but without overhauling their internal business processes to match the new xP&A capabilities and gaining access to the right data, companies are unlikely to realize the full potential of xP&A. We will address business process change at another time (it’s a BIG topic!), but in the remainder of this blog post we are going to focus on the data aspect of xP&A success, and what a CFO needs to know about it.


In simple terms, an xP&A data hub is "a relational database that sits between the source systems and planning applications." Data, gathered from various sources, is aggregated, standardized, and transformed in the data hub before being pushed out to the planning software.

The data hub is critical to modern-day, integrated planning. It sets the foundation for future forecasting and demand planning, helps trace the data to the exact source, aligns the correct tool for every use case, insulates the planning system from source system changes, cleanses and standardizes the data, and supports ad-hoc reporting.

The xP&A roadmap designed for your firm is dependent on a strong foundation of grounded and verified data. Using the planning software alone to manage troves of data from various sources can stall your xP&A developments midway. While the software is capable of providing driver-based and predictive modeling power with rich reporting abilities, it is not the optimal environment to govern large amounts of data ingested from multiple sources. Moreover, it also lacks the tools to handle different data use cases. Setting up a data hub using a relational database such as Microsoft SQL Server, can not only support the planning software by managing all the data, but it can also give easy access to data points and their sources, increasing maintainability and transparency.


Faltering on the data management piece can undermine all the advantages gained from the xP&A transformation. This happens due to many reasons.

  1. Planning software vendors tend to downplay the likelihood of facing any data issues with xP&A. Their primary focus is on software features for moving and integrating data using ETL (extract, transform, load) tools, while glossing over the effort needed to ensure data quality, trustworthiness, and completeness.
    • Some data manipulations are simply easier, cheaper, and faster to do in a data hub running on a relational database than in the planning platform, even when the planning tool has some data management capabilities. It is akin to comparing a heavy-duty screwdriver set to the screwdriver tool on a Swiss-army knife. The latter will not get the job done in every situation.
  2. The IT department can also put a wrench in the organization's plans. Here is how -
    • They might not be prepared to relinquish their roles as data managers. Despite not being familiar with new xP&A developments and their data requirements, they might stick to their guns and refuse outside help.
    • They also might fear losing their roles to new technology and become defensive.
    • They might not be familiar with working with a new technology stack and are unsure of how to proceed.
    • They might not understand the importance and value of incorporating a data hub along with the planning software.
  3. The third reason could be a lack of clarity regarding the business requirements of operating the new planning software.
    •  Executives might be familiar with the end goals but fail to understand the smaller steps that make up those goals.
    • Having ready access to copious amounts of actual data as part of determining business requirements is important, because hypotheses about the relationships between data points can only be validated with actual data. For example, understanding true relationships between products and business units, or whether GL accounts are used consistently across all geographies are important for reporting and model design.
    • Sometimes the required data does not exist in a form that can be used by the team, and may expose opportunities to strengthen data collection processes, or to modify data retention policies.


While moving towards xP&A is a necessary transformation that can help companies remain viable and thrive through disruption and uncertainty, the data issues listed above can derail this momentum at any time. Here is how to prevent data issues from derailing your xP&A initiative:

  1. Start by analyzing these risks and assessing how they affect you. Downplaying them won't help anyone. It is necessary to identify their impact and work together with your team for a solution.
  2. Do not wait for issues with data procurement, allocation, and management to arise later. Proactively address them by making the case for a relational data hub early in your xP&A roadmap, so you have the right foundations and tools available to support your success. 
    • Focus on achieving small, incremental quick wins, rather than trying to do everything at once. An incremental approach enables you to be agile and gives you room to re-assess your priorities based on what you are learning along the way. For example, suppose you start with consolidated financial reporting as your first goal. This will likely help to shorten your month-end close processes, besides providing you with validated data and automated reporting. In addition, it can serve as the springboard for your next goal, which may be expense planning. By then, your team will understand the tool much better, and you will likely need less consulting help and training. Taking an incremental approach gives you room to change course when something unexpected happens (for example, if the data you need is not ready yet). It also helps to contain costs and shorten timelines, because the ability to course-correct early reduces the likelihood of going too far down the wrong road.


Success with xP&A depends on three inter-dependent factors. The first is selecting a planning software platform that will satisfy your modeling and reporting needs. The second is to understand the effort as a business process overhaul, not just a technology implementation. And the third, which was the main topic of this blog post, is to ensure you have solid and realistic foundations in the form of an xP&A data hub to support the data strategy without which true xP&A cannot happen.

Related topic: Why xP&A is more than just marketing hype!


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