The evolution of MFP
Successful MFP transformation
Team and change management
Continuous improvement and adaptability
AI, ML, and the future of MFP
Merchandise Financial Planning (MFP) serves as a vital bridge between a company's financial targets and its merchandising and marketing strategies. MFP has undergone significant evolution in recent years due to advances in technology and the ever-changing retail landscape. In this aim10x webinar, Brad Eckhart, Partner at Columbus Consulting, and Anjali Burkins, Director of North America Retail Strategy at o9 Solutions, explore the MFP process, its evolution, the role of technology, and the impact of artificial intelligence (AI) and machine learning (ML) on the future of MFP.
At its core, MFP ensures the alignment of a company's financial goals with the category-level plans that support merchandisers' visions. It harmonizes financial targets with merchandising and marketing strategies by defining strategic targets that can be then broken down by Product Class, by Channel and by Geography to drive the shorter term planning areas such as assortment planning and allocation and replenishment. MFP has evolved from primarily focusing on top-down category planning to encompassing more granular aspects and adapting to the dynamic requirements of retailers. Considering these shifts, companies are now seeking solutions to help address these challenges as well as enhance automation and collaboration to refocus energy on strategic planning.
The evolution of MFP: responding to retail changes
The retail industry has experienced a profound transformation, fueled by the rise of e-commerce and the shift towards omni-channel strategies. In the past, online and brick-and-mortar businesses operated independently, with separate planning and allocation organizations.
However, the rising adoption of e-commerce and the recognition of the omni-channel approach shattered these silos. Retailers began managing inventory across channels, understanding the origins of demand, and harnessing digital platforms to build their brand. This shift required significant changes in planning organizations, business processes, and systems to support evolving business models.
While Excel has long been a favored tool for merchandise financial planning due to its flexibility and familiarity, its limitations became apparent as retail complexities grew. Retail organizations reached a tipping point where the need for faster decision-making, increased plan accuracy, improved collaboration, and enhanced workflow outweighed the capabilities of Excel. This led to the adoption of more sophisticated planning systems, either standalone merchandise financial planning systems or integrated planning systems that encompass multiple planning types.
Data analytics, the foundation of successful MFP
Data analytics have gained significant traction in the retail industry. Data plays a critical role in MFP, empowering retailers to derive insights and make more informed decisions. Establishing clean and reliable data through master data management and data architecture lays the foundation for effective data analytics. Data modeling continues to play a significant role in forecasting and supporting the MFP process. By analyzing customer data, demographic information, and store sales data, retailers can create tailored assortments, understand customer preferences, and enhance planning accuracy. Attributes and hierarchy also play a crucial role in effective planning, making consistent master data governance across the organization is essential to effective MFP.
The keys to a successful MFP transformation
To successfully transform the MFP process, organizations must establish a clear vision of the desired future state. Defining what the planning process should look like and how the organization should operate is crucial. While flexible planning systems can be tailored to specific requirements, aligning technology with the overall vision is paramount. Additionally, establishing reliable and clean data, embracing data analytics, and fostering a data-driven culture are vital components of a successful MFP transformation.
The irreplaceable role of the team and change management
A successful MFP transformation relies on assembling the right team. Skilled individuals with a deep understanding of the planning process, data analytics, and technology are essential for driving the transformation forward, and these team members can effectively leverage planning systems, interpret data insights, and collaborate with stakeholders across the organization.
Change management also plays a vital role in MFP transformation. Implementing new processes and systems often requires changes in workflows, roles, and responsibilities, and having a comprehensive change management plan in place ensures a smooth transition and minimizes disruption. Effective communication, training, and ongoing support are crucial to helping employees adapt to new ways of working and embrace the benefits of the transformed process.
Continuous improvement and adaptability
The retail industry is characterized by constant evolution, demanding agility and adaptability in the MFP approach. Regularly monitoring the effectiveness of the MFP process, collecting feedback, and making necessary adjustments are essential to ensure ongoing alignment with the organization's goals and the evolving business landscape. Assessing and optimizing assortment strategies, demand forecasting accuracy, and other planning components enable retailers to stay competitive and meet customer expectations.
Looking ahead: AI, ML, and the future of MFP
One of the ways to unlock the full potential of MFP is through the integration with demand planning and assortment planning and the use of AI and ML, which also enables the ability to automate data analysis. Retailers deal with vast amounts of data, including customer data, sales data, and market trends. AI and ML algorithms can efficiently process and analyze this data, uncovering valuable patterns and insights that human analysts may overlook. By leveraging AI and ML, retailers can gain a deeper understanding of customer preferences, identify emerging trends, and make data-driven decisions that drive profitability.
Forecasting accuracy is a critical aspect of MFP, and AI and ML play a significant role in improving this accuracy. Traditional forecasting methods often rely on historical data and manual analysis, which may not capture the complexity and dynamics of the retail landscape. AI and ML algorithms, on the other hand, can consider numerous factors, such as seasonality, market trends, and external influences, to generate more precise demand forecasts. These accurate forecasts enable retailers to optimize inventory levels, minimize stockouts, and maximize sales, resulting in improved financial performance.
Personalization is of increasing importance to the retail sector, and AI and ML enable retailers to deliver tailored merchandising strategies. By analyzing customer data, demographic information, and purchasing patterns, AI and ML algorithms can recommend optimal assortment strategies and promotional offers that resonate with individual customers. This personalized approach enhances the customer experience, fosters customer loyalty, and drives sales.
It is important to note that incorporating AI and ML into MFP requires a foundation of reliable data and robust data governance practices. Clean and accurate data is essential to train AI and ML models effectively and ensure the validity of their outputs. Retailers must prioritize data management, including data quality, privacy, and security, to derive meaningful insights and maintain trust with customers. While AI and ML offer tremendous potential in MFP, it is also important to recognize their limitations as tools that augment human decision-making (rather than replace it). Human expertise and domain knowledge remain crucial in interpreting and contextualizing the outputs generated by AI and ML algorithms. Retailers should leverage the strengths of both human intelligence and machine intelligence to make informed and strategic decisions in merchandise financial planning.
In conclusion, collaboration, demand forecasting, omni-channel inventory management, real-time analytics, and supply chain integration are crucial components of merchandise financial planning in the ever-evolving retail landscape. By embracing these aspects and staying attuned to the potential of AI and ML, retailers can unlock new opportunities for growth, improve customer satisfaction, and maintain a competitive edge. The continuous evolution of merchandise financial planning, driven by technology, has become an indispensable component for retailers aiming to succeed in an ever-changing marketplace.
Webinar: A Future-proof approach to Merchandise Financial Planning
By providing a comprehensive view of a retailer’s operations, MFP enables better, faster decision-making about pricing, promotions, and inventory allocation to maximize profitability and minimize risk. Gain actionable insights and best practices for successful MFP implementation and utilization from industry experts.
About the author
Santiago Garcia-PovedaRetail Digital Transformation Leader
Santiago holds a Master in Civil Engineering from Universidad Politécnica de Madrid and Ecole des Ponts, and an MBA from Haas - University of California, Berkeley. In o9 Solutions, Santiago leads our strategy for the retail industry, bringing his expertise on the industry needs, guiding the product development efforts, and engaging with industry executives to advise on their digital transformation. Before o9 Solutions, Santiago worked for McKinsey & Company for 8+ years serving. Business to Consumer clients (apparel, groceries, hardlines, and CPGs) globally on their Digital and Analytics challenges across multiple areas of their business (supply chain, commercial, procurement, …). Additionally, Santiago also has industry experience from working as Director of Business Transformation in Adidas Outdoor, a corporate strategy for Esprit, focused on accelerating the product delivery process and increasing the collaboration with wholesale partners.