Qualitative forecasting method specially Delphi method

1. SUBMITTED TO
DR VISHAKHA KUTUMBLE
3rd Internal assignment
QUALITATIVE FORECASTING
{DELPHI METHOD}
Business forecasting & planning techniques
SUBMITTED BY
CHETAN
VIPUL SETHIYA
MBA (BUSINESS ECONOMICS)
4TH 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:
1) Assembling a panel of experts,
2) Conducting an initial survey to gather individual
forecasts and rationale,
3) Providing anonymized feedback to the panel,
4) Facilitating multiple rounds of discussion and re-
evaluation, and
5) 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.