December 4, 2023 By Rodrigo de Andrade 3 min read

In the rapidly-evolving business ecosystem, many companies face a combination of challenges, including inflation, supply chain disruptions and a complex labor market. These factors exert significant pressure on profitability. In this scenario, traditional planning methods may hinder a company’s ability to respond quickly and strategically to changing opportunities and challenges.   

This is where autonomous planning shines. This approach empowers organizations to utilize data-driven analytics, artificial intelligence (AI) and automation to make well-informed decisions swiftly and accurately, enabling them to navigate the complexities of the modern marketplace with agility and precision.  

 At its core, autonomous business planning comprises innovative methods that leverage the potential of cutting-edge technologies such as foundation models and generative AI. It empowers businesses in their sales planning, budgeting and forecasting processes. The goal is not to replace individuals but to empower them to focus on the strategic aspects of the business. This approach can handle a significant number of tasks with minimal or no human intervention.   

 What distinguishes autonomous business planning from traditional automation is its ability to provide augmented, predictive and prescriptive insights and automate tasks based on these insights. This not only enhances agility, but also has the potential to significantly reduce the time required for decision-making.  

Common challenges in today’s business planning 

As data becomes more accessible, companies recognize the importance of using it for business and financial planning. Despite the availability of advanced technological solutions, companies often face significant challenges when using planning and analytics tools. Three of the most prevalent obstacles include:  

Excessive time consumption  

Finance professionals spend an excessive amount of time on manual tasks, leading to a prolonged business planning process. They primarily engage in repetitive tasks, leaving insufficient time for data analysis and its evolution.  

Inaccurate planning and forecasting  

When decision-makers base their choices on unreliable projections and estimations, it can impact the organization’s overall strategic direction, leading to undesirable outcomes such as misallocation of resources, missed growth opportunities and even financial instability.  

Adoption barriers  

The steep learning curve associated with planning tools can restrict overall adoption and hinder their effective use in supporting budgeting, investments and forecasting planning. Consequently, this can lead to unfavorable financial outcomes, missed growth opportunities and increased financial risks for the company.  

Generative AI shapes business planning   

Generative AI and foundation models have completely transformed the landscape of business and society. What seemed impossible and futuristic just a few years ago is now a tangible reality, propelling us into a historic and disruptive moment.  

According to Alex Bant, Vice President of Gartner’s Finance Practice, “Generative AI can explain forecast and budget variances for financial planning and analysis teams to use in business reviews. It can also synthesize those trends and insights for executives and the board.”

Additionally, it represents a groundbreaking paradigm shift in various aspects of business planning processes. One of its significant impacts lies in its ability to provide a natural language interface, bridging the gap between complex financial data and end-users, thus elevating planners to advanced users by automating complex tasks and rapidly providing insights and guidance. Users now have the ability to ask questions about a given situation and receive detailed, informative responses. 

For instance, when users create their plans, they can examine past results and inquire with the assistant about the reasons for a sudden increase in expenses in the previous year. The assistant can then provide visualizations and text explanations, attributing the increase to factors like seasonality, specific events or even suggesting potential data entry errors. Users can define thresholds and conditions for identifying anomalies or adjust their plans and strategies accordingly. 

This enhanced user-friendliness has the potential to accelerate productivity and establish a competitive edge, enabling businesses to respond more quickly to market dynamics.  

 IBM Planning Analytics meets generative AI  

IBM Planning Analytics can automate integrated business planning across your organization, streamline processes and foster collaboration across your teams to quickly respond to market disruptions.  

IBM Planning Analytics is set to undergo a transformative phase with the introduction of generative AI. This enhancement offers the opportunity to revolutionize the business planning workflow and support companies in enhancing their efficiency, leading to more accurate and strategic marketing decisions.  

The future inclusion of a natural language AI assistant is strategically planned to reduce usage barriers by offering an intuitive and effortless interaction with Planning Analytics. This enhanced experience not only grants users access to valuable information and insights but also empowers them to engage with their data in a more user-friendly and intuitive manner.

For instance, a user might ask, “How do I create the best employee schedule that balances workload and reduces labor costs?” With the envisioned integration with foundation models, IBM Planning Analytics, which has been providing prescriptive insights since 2021 through integration with IBM Decision Optimization (IBM® ILOG® CPLEX®), can interpret the user’s request, analyze relevant data and parameters, and provide a suggested schedule along with natural language explanations.  

 IBM envisions AI serving as an advisory partner, utilizing advanced optimization techniques to propose optimal strategies and recommend precise actions and decisions that can contribute to achieving expected results and minimizing risks in complex business scenarios.  

Read the ‘IBM Planning Analytics and the future with generative AI’ paper 4 ways to empower small and medium businesses with generative AI

Important: IBM may change or withdraw statements regarding its future direction and intent without notice. These statements represent current goals and objectives only.  

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