Qualitative-Analysis (Business-Forecasting) Nestle.pptx

Qualitative forecasting method specially Delphi method

1. SUBMITTED TO DR VISHAKHA KUTUMBLE 3 rd Internal assignment QUALITATIVE FORECASTING {DELPHI METHOD } Business forecasting & planning techniques SUBMITTED BY CHETAN VIPUL SETHIYA MBA (BUSINESS ECONOMICS) 4 TH SEMESTER

2. Qualitative Analysis in Business Forecasting: A Case Study on Nestlé Nestlé, the renowned global food and beverage company, has long recognized the importance of effective business forecasting in navigating the ever-changing market landscape. In this presentation, we will explore how Nestlé has leveraged the power of qualitative analysis, particularly the Delphi method, to enhance their forecasting capabilities and drive strategic decision-making.

3. Introduction Nestlé, founded in 1866, has grown to become one of the largest food and beverage companies in the world, with a presence in over 190 countries. Known for iconic brands such as Nespresso, KitKat, and Nescafé, Nestlé's success is largely attributed to its ability to anticipate and adapt to market trends and consumer preferences. Business forecasting plays a crucial role in this process, allowing Nestlé to make informed decisions and maintain its competitive edge. Accurate forecasting is essential for Nestlé to effectively manage its supply chain, optimize production, and allocate resources efficiently. By leveraging qualitative analysis techniques, Nestlé can gain valuable insights into the future, ultimately enhancing their decision-making capabilities and driving sustainable growth.

4. Objective The primary objective of this case study is to demonstrate the application of qualitative analysis, specifically the Delphi method, in Nestlé's business forecasting process. By examining Nestlé's implementation of this approach, we aim to illustrate the benefits and challenges of using qualitative techniques to inform strategic decision-making in a complex, global business environment.

5. Qualitative Analysis Overview Definition and Importance Qualitative analysis is a critical decision-making tool that goes beyond numerical data, focusing on the collection and interpretation of non-numerical information. In the context of business forecasting, qualitative analysis allows companies to incorporate expert opinions, industry trends, and subjective insights into their decision-making processes. Qualitative Methods Nestlé has explored various qualitative methods to enhance their forecasting capabilities, including the Delphi method, expert judgment, scenario analysis, and focus groups. Each of these approaches offers unique strengths and can be tailored to specific forecasting challenges. Benefits of Qualitative Analysis By leveraging qualitative analysis, Nestlé can gain a deeper understanding of market dynamics, consumer behavior, and industry-specific factors that may not be fully captured by quantitative data. This holistic approach helps the company make more informed, nuanced decisions that drive long-term success.

6. The Delphi Method 1 Overview The Delphi method is a structured, iterative forecasting technique that relies on the collective expertise of a panel of subject matter experts. This approach aims to achieve consensus through a series of anonymous questionnaires and feedback rounds, allowing participants to refine their judgments and provide valuable insights. 2 Implementation Steps Nestlé's application of the Delphi method typically involves the following steps: Assembling a panel of experts, Conducting an initial survey to gather individual forecasts and rationale, Providing anonymized feedback to the panel, Facilitating multiple rounds of discussion and re-evaluation, and Reaching a consensus on the final forecast. 3 Advantages and Limitations The Delphi method offers several advantages, such as its ability to leverage diverse perspectives, reduce bias, and foster collaborative decision-making. However, it also faces limitations, including the potential for participant attrition, the time-consuming nature of the process, and the subjectivity inherent in expert judgments.

7. Application to Nestlé Forecasting Challenge Nestlé faced a unique forecasting challenge in predicting the demand for a new line of plant-based protein products. With rapidly evolving consumer preferences and an increasingly competitive plant-based market, the company recognized the need for a more sophisticated forecasting approach to guide its strategic planning and resource allocation. Delphi Method Implementation Nestlé assembled a cross-functional panel of experts, including market analysts, product development specialists, and industry thought leaders. Through a series of structured surveys and feedback rounds, the panel examined market trends, consumer insights, and potential scenarios to arrive at a consensus forecast for the new plant-based product line. Key Insights The Delphi process enabled Nestlé to gain valuable insights, including the anticipated rate of market adoption, the potential impact of emerging competitors, and the optimal pricing and positioning strategies. These insights were crucial in informing Nestlé's strategic decision-making and resource allocation for the plant-based product launch.

8. Results 1 Forecast Accuracy The Delphi-based forecasting process demonstrated a high level of accuracy, with the final consensus forecast aligning closely with the actual market performance of Nestlé's new plant-based product line. 2 Competitive Positioning The insights gained from the Delphi method enabled Nestlé to adjust its product pricing, marketing messaging, and distribution strategies, allowing the company to effectively compete in the rapidly evolving plant-based market. 3 Strategic Decision-Making The forecasting results directly informed Nestlé's strategic decisions, such as expanding production capacity, investing in targeted marketing campaigns, and exploring new partnership opportunities to further strengthen its position in the plant-based protein segment.

9. Impact on Nestlé Enhanced Agility Nestlé's successful application of the Delphi method in forecasting the plant-based product demand has enabled the company to become more agile and responsive to market changes, allowing it to adapt its strategies and operations accordingly. Improved Resource Allocation The accurate forecasts derived from the Delphi process have helped Nestlé optimize its resource allocation, ensuring that investments in production, marketing, and distribution are aligned with the anticipated demand, thereby improving overall efficiency and profitability. Strengthened Competitive Edge By leveraging qualitative analysis through the Delphi method, Nestlé has been able to gain a deeper understanding of consumer trends and market dynamics, allowing the company to make more informed strategic decisions and maintain its competitive advantage in the plant-based protein segment.

10. Conclusion Nestlé's case study demonstrates the valuable role that qualitative analysis, particularly the Delphi method, can play in enhancing business forecasting capabilities. By tapping into the collective expertise of a panel of industry experts, Nestlé was able to gain crucial insights that informed its strategic decision-making and ultimately drove the successful launch and growth of its new plant-based product line. As companies navigate an increasingly complex and rapidly evolving business landscape, the integration of qualitative analysis techniques, such as the Delphi method, can provide a crucial competitive advantage. By combining the power of expert knowledge, collaborative decision-making, and a structured forecasting process, organizations can make more informed, data-driven decisions that lead to long-term success.