Trends in FP&A for 2021

Trends in FP&A for 2021

2020 presented a cohort of new challenges for companies.  Finance teams battled with unbridled uncertainty as they attempted to cope with the ‘new normal’. Needless to say, financial planning & budgeting, cashflow forecasting and scenario analysis had to undergo a paradigm shift in order to continue delivering meaningful insights to stakeholders. The only ‘North Star’ in such a situation was a highly automated planning function supported by a strong technology stack. Teams that possessed the necessary tech stack aligned themselves faster to the new normal. The situation of those caught unawares can be summarized with the following facts:

  •  42% of their time was spent on low value activities.
  • Only 26% of their time on an average was spent on insight generation.
  • These shortcomings were among the key reasons that prevented the FP&A teams from being true strategic advisors.

The irrevocable fact that FP&A teams can no longer ignore, is that their functioning needs to be agile. They must ensure continuity through well-integrated systems and processes. Teams must constantly work to keep themselves up-to-date with the constant technological upgrades. An instance in this regard is that even today, very few companies possess integrated data systems which means, not only is there a time lag in extracting insights but also the decisions are not necessarily supported by data driven insights. A pertinent question which thus rises is, what will FP&A teams be doing when looking for ways to eliminate such gaps?

  1. Shifting to Cloud

A survey conducted at the end of 2020 concluded that usage of Cloud reliant solutions can reduce companies’ dependency on spreadsheets by three-fourths while improving productivity by about 40%. The selling point of cloud based systems is their adaptability. They are easy to set-up, handle, and modify. Their central database makes it easier to consolidate and validate data, thus allowing for greater time spent on insight generation as well as better forecasting accuracy. Most importantly, they can utilize real-time data promptly, to make changes in report generation and facilitate scenario analysis. Thus, they allow for a much more agile planning process.

To take this one step forward, teams can construct bespoke tech stacks. For instance, on the Cloud infrastructure, an application layer of Tableau, MySQL, Host Analytics or Qlik can be installed for quick reviews and visualization. On this, a process layer can be installed to clean data, create custom dashboards and monitor for continuous improvement. At the very top, can be the service layer which provides comprehensive and scenario-wise analysis. Such operating models are increasingly being adopted by fast growing companies, especially tech companies. 

  1. API Integration

API Integration  between different platforms, applications and systems takes into account business specific needs and reorganizes the inter-relationship between different software. Businesses that fail to employ API integration are missing out of its many advantages including, but not limited to, reduced costs, streamlined business operations and better customer experience.

API integration reduces barriers to innovations, opens doors to a wider range of possibilities and allows better contribution of a company’s resources to its success. The age old reliance on outdated and expensive measures is no longer sustainable in the age of digital transformation. Pioneering companies will gradually begin moving toward API Integration to build the best solutions. Some popular platforms for API integration are and

  1. Continuous Planning

Continuous planning is the chassis for smarter and faster decision making. This method replaces static bi-annual or annual plans with continually updated ones. These allow businesses to swiftly adjust to any internal or external event. In recent times, many teams are facing challenges with respect to topline management, expenses, planning, etc. The only way businesses can deal with the uncertainty caused by such challenges is deploying the right technology to facilitate rapid planning and review cycles. 

Continuous planning is inclusive of such progressive mechanism. It includes re-forecasting, what-if scenario analysis and mostly importantly, producing actionable insights from such rapidly shifting analysis. The method significantly compresses cycle time, eliminates errors and enables seamless information flow. The goal is to create a connected and collaborative environment.

  1. Machine Learning and Artificial Intelligence

We are on the cusp of witnessing a massive, AI facilitated upgrade to Digital FP&A. On the planning side, a combination of these can be used to create a baseline forecast. Additionally, they can augment the FP&A process by cutting down the time spent on non-value add activities and using real-time data for planning. The goal is to free up the capacity for teams to focus on insights rather than starting from scratch for every fresh data feed. Very few FP&A teams are currently using AI although this number is predicted to grow in the future.

Currently, a popular e-commerce company makes use of machine learning for revenue forecasting. The constant disposal of vendor agreements and creation of new agreements to supersede the previous agreements had driven significant efforts towards re-working. By using a machine learning model, FP&A teams ended up saving precious time.

However, different companies need different financial tools depending on their sector and stage of growth. Although switching to cloud or using AI sound compelling, they are not a panacea for all stages of maturity of FP&A teams.

  • Teams in their nascent stages, those which have been performing just the accounting function and only recently started exploring with forecasting and improved analysis. Their reliance being primarily on spreadsheets, these teams will need external assistance in the form of business-relevant and sophisticated financial models.
  • FP&A teams with mid-stage levels of maturity typically use spreadsheets for analysis along with a system for forecasting and budgeting. The issue here is that the data is stored in a separate, often non-standard format making it difficult to filter the analysis as desired.

An example in this regard is that of a growing B2C SaaS company that realized that handling multiple spreadsheets with data growing in tandem was a tedious task. Their solution was to create workflow diagrams for every data point which moved between spreadsheets to conclude whether they would like to retain the data-point as they developed a new system. This system was then transitioned to a third-party, cloud-based application which incorporated advanced functions such as AI.

  • At the final stage of maturity, FP&A teams can automate and improve the efficiencies of budgeting and planning and integrate revenue analytics on a real-time basis. Not only does it reduce the scope for error but also ensures accurate data usage for modelling, better analytics and reporting.

Digital transformation is only the first step in moving toward the goal of integrated FP&A. To pave the way for truly collaborative planning, having no silos in the organization is key. This will require some introspection on the organization’s part. Some relevant questions are:

  •  What is your current FP&A approach?
  • How agile  is your planning system?

Are you ready for the transition from FP&A to XP&A?


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