Successful planning with AI in Finance: Why your planning process needs a transformation.

Successful planning with AI in Finance: Why your planning process needs a transformation.

Is your financial planning process agile enough for today’s volatile market? This article explores why traditional methods fall short and introduces a smarter, AI-driven approach for more resilient and efficient financial planning.

The traditional planning process does not meet the requirements of today’s market environment 

Financial planning today, whether with respect to financial forecasting or the target setting subprocess, often falls short of meeting the requirements of the rapidly evolving market landscape and its demand for fast and effective decision making. There are three core issues: 

  1. Vulnerability to Human Error and Biases: The process heavily relies on manual data collection, analysis, and decision-making. This labor-intensive approach introduces a significant risk of human errors and biases. These human biases, whether with respect to overconfidence or caused by deviating incentives of the people who are involved in the process (principal – agent), negatively impact the accuracy of financial forecasts.
  2. Inefficient Resource Allocation: The extensive manpower required for the countless manual steps of the planning processes makes financial planning a costly endeavor with a large optimization potential. The budgets which are allocated for financial planning processes frequently don’t align with the actual value generated. The introduction of technological innovations and AI-supported automation can drastically optimize resource spending. 
  3. Excessive Attention to Detail: The common attention to minor details is very time-intensive without generating significant added value for the overall planning quality. Detailed planning of irrelevant accounts or excessive focus on small deviations diverts the attention from steeringrelevant financial metrics and decisions. 

Traditional financial planning is slow, costly, and prone to errors, making it inadequate as a process which can adapt to swift market changes. This results in missed opportunities and is putting the company at a competitive disadvantage. 

The way forward in times of rapidly changing markets? AI-based financial planning

Transforming the planning process by leveraging AI-based technologies offers the potential to align costs and benefits, enhance accuracy, reduce bias, improve efficiency, and enable proactive and resilient financial planning in an ever-changing market environment. 

What an innovative, AI-supported financial forecasting process looks like

Now that we’ve identified the challenges at hand, let’s shift our focus to the innovative solution. We view the transformation of the financial forecasting process through the lens of two distinct roles: the Traditional Controller and the Analytics Controller. The Traditional Controller is the backbone of today’s financial planning, burdened with manual tasks and limited by the tools at hand. The Analytics Controller embodies the future of financial planning – an agile, AI-augmented role which focuses on strategic analysis and data-driven decision support.

What does a day of a Controller within the forecasting period look like? An Illustrative example.

What does a day of a Controller within the forecasting period look like? An Illustrative example. 

1st Day of the forecasting process 

Trained to understand the necessary inputs and outputs of AI-supported forecasting, the Analytics Controller reviews the latest forecast and evaluates whether any adjustments to the input data are necessary. The remaining time is used to analyze relevant business developments, define focus areas for the upcoming forecasting process and generate first insights. The Traditional Controller is collecting data. 

2nd Day of the forecasting process 

The AI-supported financial forecast is readily accessible by the second day of the forecasting process, after being generated by the Analytics Controller through the simple click of a button. Forecasts are evaluated right away, stakeholders are informed, and reviews are conducted. Unexpected developments are discussed, additional insights are generated on demand. By leveraging simulation capabilities, different market developments are outlined to provide scenario analyses for causal explanations and strategic considerations. The Traditional Controller is still collecting data. 

5th Day of the forecasting process 

The evaluated, reviewed, and enhanced forecasts are presented to the management by the Analytics Controller. Following the recommendations forhandling of unexpected changes, measures can be decided, and further analyses are conducted to provide deeper insights into key positions. Management and controlling proactively prepare for upcoming market developments by discussing the simulated scenarios and their expected impact on the organization. The Traditional Controller is still collecting data. 

10th Day of the forecasting process 

The forecast as well as the proposed measures are already communicated to the affected areas and teams. A comprehensive report is available which provides the foundation for all stakeholder communication. The Analytics Controller is monitoring the adoption of the proposed measures and as well as the real-time development of the company’s KPIs. The Traditional Controller is starting the forecasting process. 

We provide guidance throughout your entire transformation process 

Adopting AI in your financial planning process isn’t merely an option – it’s becoming a necessity. But how can you get there? Industry trends suggest that AI-driven financial operations are the future, and starting your transformation now is crucial to stay competitive. Transforming your financial planning with AI is simpler than you think. We recommend a tactical execution in four clearly defined phases to align the transformation process with your organization’s readiness: 

  1. Start with a strategic assessment, to evaluate your existing planning systems and unite your leadership team around a common vision for an AI-empowered future. 
  2. Continue with the Minimum Viable Product phase. Select the most suitable AI technologies and the most promising processes to initiate a first use case. Implement it step by step. 
  3. Scale with a Gradual Expansion. The transformation to an AI-augmented organization is an ongoing process. Start from the successful MVP and continuously expand the scope to scale your AI strategy across the organization. 
  4. Incorporate training as catalyst for success. Define clear steps and actions as key components of your transformation journey, with a strong focus on enhancing the organization’s skill base

To ensure long-term success and adaptability, the shift to financial planning with AI should not be seen as a onetime project – it’s a strategic evolution. Don’t get left behind in an environment which is rapidly moving forward. Seize the opportunity to build a more efficient, accurate, and proactive financial planning process. Start today! 


Anja Lutz

Tanja Aue
ConsultantAdvanced Planning 

Tanja Aue is Consultant for Advanced Planning with a dual masters degree in finance and information systems and 3 years of experience in finance advisory and IT. Tanja specializes in digitalization and automation, harnessing advanced analytics to optimize financial processes, effectively bridging the gap between business requirements and technical design.

Are you interested in the transformation of your financial processes? Contact us today to start your journey to the financial process landscape of the future! 

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