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Operation Managment - Demand Forecasting

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BSO214SL - Operations Management
Coursework 1 – Operations Strategy
Demand Forecasting
Table of Contents
1.
Executive Summary................................................................................................................. 3
2.
Introduction ............................................................................................................................. 4
2.1.
Introduction to Nestle .......................................................................................................... 4
2.2.
Introduction to Unilever ....................................................................................................... 5
2.3.
Introduction to Topic – Demand Forecasting ...................................................................... 6
3.
Understanding the practical application in a company setting ................................................ 7
3.1.
Nestle ................................................................................................................................... 7
3.2.
Unilever................................................................................................................................ 9
4.
4.1.
Critically comment on the application................................................................................... 12
Comparing and Contrasting the two companies ................................................................ 12
5.
Difficulties, Recommendations, and Possible Improvements. .............................................. 14
6.
Conclusion ............................................................................................................................. 16
7.
Referencing ............................................................................................................................ 17
1. Executive Summary
This report aims to study the practical and theoretical implications of an operation strategy in two
companies in the same industry. It is mainly focused on the comparison between the selected
companies which is Nestle and Unilever. It is regarding how the demand forecasting process is
carried out in an overall view. This report determines the practical application and methods used
by the companies in the planning process, used to forecast their future sales. A fair comparison
between the two companies regarding how the process is carried out is also described. Similarly,
difficulties faced during the process and possible ways of reducing the complications are revealed.
Interviews were conducted with the demand planners of Nestle and Unilever. The main focus of
the report was to identify the different methods followed by each organization. The result of each
interview provided a general idea about the process followed to accurately forecast their sales. It
was found that the processes followed were quite similar with just a few variations.
It was found that Nestle follows an eighteen-month horizon and runs on a monthly bucket forecast
whereas Unilever has a three-year long-term plan, one-year accurate plan, and a weekly bucket
forecast. In conducting the procedures, Nestle uses Multi- Business Plan (MBP) while Unilever
follows the Sales and Operation Plan (S&OP).
Another main focus was to identify the difficulties faced in the procedure followed. Both
organizations suggested that depending on just historical data was quite a risk, as unexpected
events could occur which creates difficulties and alteration in the process. Also, certain unexpected
clarification and incidents when carrying out meetings create conflicts, worries, and complications
within the organization itself.
Either way, results from both organizations showed that they manage to smoothly run the demand
forecasting procedures. Unforested and unexpected events are immediately brought into attention
and possible rearranging and re-planning the forecast is conducted while maintaining peace within
the organization.
2. Introduction
2.1.Introduction to Nestle
Nestle is recognized as the world’s largest food company founded by Henri Nestle back in 1866.
The company has worded its purpose as "Enhancing the quality of life and contributing to a
healthier future. Driven by our purpose we want to help shape a better world and inspire people to
live healthier lives. This is how we contribute to society and ensure our long-term success"(Nestle,
2019). Since 1866, Nestle has grown widely with currently over 330,000 employees working at
469 different locations in 86 countries, making over 90 billion annual revenues (Armstrong, 2013).
Nestle is now emerging as the world’s leader in health, nutrition and wellness providing “Good
Food, Good Life” to its consumers and customer. Food and beverages are an important part of
people's lives as in, not only terms of personal health and nutrition but also as it provides the
societal desire of eating together. Nestle provides good quality and highly safe products which are
of good value to the money paid and convenient in the daily life of people hence consumers highly
appreciate nestle products over other similar product in the market (The World of Nestle, 2016).
Nestle builds consumer belief equally in the company and its products which is the main reason
behind success and growth. Getting close with consumers and understanding them in different
aspects, studying their needs and wants "The consumers at the heart are all we do" is a method
nestle uses to ensure that products are manufactured to suit all types of people from babies,
teenagers and adults (The World of Nestle, 2016).
Nestle manufactures local food as they believe local food and local experience is the main focus
on increasing its market share. Nestle leads both global and local markets with over ten types of
products namely milk and dairy products, nutrition, ice cream, breakfast cereals, coffee and
beverages, culinary products, chocolate and confectionery, pet care, bottled water (The World of
Nestle, 2016). Nestle believes in the long term, mutual partnerships with their suppliers and retail
trade customers and hence does not own any farm of their own instead focus on transforming raw
materials in high quality and safe products ready to be consumed (The World of Nestle, 2016).
Nestle grows daily and is globally recognized. The usage of these several techniques drives them
to be the best within the product markets.
2.2. Introduction to Unilever
Unilever has more than 400 brands and does its selling in more than 190 different countries around
the world. It can also be identified as one of the leading companies which have gained consumer
attraction in many ways. Unilever is also recognized as a Fast-Moving Consumer Goods company
(FMCG), which offers around 29 leading brands globally (Sri Lankan Export Development Board,
2019). Home Care, Personal Care, and Food can be identified as examples for them. Moreover,
Unilever was established in the early '90s and started with brands such as Sunlight, Lux, and Pears
and has expanded its products globally. Further, Unilever does 95% of its products locally and has
been able to become one of the largest advertisers in the world (Unilever, 2019).
Further, Unilever is focusing on increasing its social impact positively by working towards social
wellbeing and by improving people’s health within 2020. It also focuses on doing green projects
to protect the environment across the world (Sri Lankan Export Development Board, 2019).
Unilever also believes a seat must be given to all women to improve the growth of the nation (Sri
Lankan Export Development Board, 2019).
These products are used to make lives easier, it makes people “look good, feel good and get more
out of life” (Unilever, 2019). Unilever owns over 13 of the world’s best 50 brands and has a
complex global value chain around the world. It has spread its manufacturing plants over sixtynine countries which consist of around three-hundred factories for production and spends
approximately three billion on raw materials and ingredients and around thirty-four billion on
goods and services (Annual reports, 2019). Unilever is also the second-largest advertiser in the
world, based on media spend (Unilever, 2019).
Unilever has employed over 155,00 employees in over 100 countries who work together to achieve
a common goal. Unilever has a clear purpose “to make sustainable living commonplace. We
believe this is the best way to deliver long-term sustainable growth” (Annual reports, 2019). All
workers share common insights and innovative ideas according to the modern trend patterns thus
increasing the market demand and sales in the organization (Unilever, 2019). Hence, Unilever is
one of the most successful organizations in the market place, globally and locally which makes
them outstand within a market place.
2.3.Introduction to Topic – Demand Forecasting
Demand Forecasting is the process of analyzing past data and predicting a possible demand for the
future (Thomas Industry Update, 2019). Simply, it is a method used to calculate and estimate the
possible demand for a product or service. This is important to companies as it allows companies
to accurately forecast annual revenue and match inventory systems while improving profit
margins. In aspects of achieving business objectives, demand plays a vital role as many decisions
such as production, and sales depend on it. Nevertheless, forecasting is a necessity of any business
at both domestic and international levels (Demand Forecasting, no date). In the words of Cundiff
and Still, "Demand forecasting is an estimate of sales during a specified future period based on the
proposed marketing plan and a set of particular uncontrollable and competitive forces."
Statistical methods are used to generate supply chain forecast, this is essential to avoid stock-outs
or overstocks and ensure customers are satisfied (Anaplan, 2019). Demand forecasting is done
according to three time periods, as stated by Nitisha (no date), there are short term forecast, long
term forecast, and very long-term forecast made by the organization. Demand planners analyze
past data thorough many algorithms and choose the method which has the least error to forecast to
the future. Historical data itself would not be enough when doing a forecast, hence companies use
opinions of manufacturers, distributors, and customers to get a border idea about the demand and
changes in trend (Thomas Industry Update, 2019). The most current data is used to examine the
future demand and make an informed decision, the process of demand forecasting is run several
times to reduce the risks and percentage error, the data is re-examined (Thomas Industry Update,
2019). These methods will allow the implementation of an effective and efficient demand forecast
process for the required time period forecasted.
Demand forecasting helps in so many different aspects of an organization. In short term, it benefits
in preparing the budget, stabilizing the employment and production, expanding and developing the
organization, makings management decisions, and evaluation performance while controlling sales,
price policy, and finance (Nitisha, no date). As mentioned by Nitisha (no date), several factors
influence demand forecastings such as the type of good which is forecasted for, consumption level,
price of the goods, technology level and the viewpoint of the economy. Demand planners forecast
for an organization through the consideration of all the factors.
3. Understanding the practical application in a company setting
3.1. Nestle
Nestle is an organization that mainly focuses on health and nutrition along with wellness which
involves the production, manufacture, and supply of numerous numbers of items in the market
place today (CNN Business, 2019). The company products include prepared dishes and cooking
aids, milk-based products, pharmaceuticals, and ophthalmic goods, baby foods and cereals,
powdered and liquid beverages, water, milk products and ice cream, nutrition and health science,
prepared dishes and cooking aids, confectionery, and pet care (Nestle, 2019). Another segment of
the business is Nespresso, Nestle Health Science and Nestle Skin Health (CNN Business, 2019).
Nestle runs demand forecasting in a four-cycle process, where all the demand related concerns are
captured and taken into consideration. A management meeting is apprehended to consider
strengths, weaknesses, and expectations. Nestlé revitalizes its demand prediction procedure,
depend on analytics to foresee the demand for low-volatile products. This gives planners more
time to estimate the demand for promotions and instable products (Armstrong, 2013). The demand
forecasting process in Nestle is carried out on an eighteen-month horizon, where past historical
data are taken into consideration and through analyzing that data, trends and impacts are quantified
and out of trend production lines are eliminated from future production. Nestle runs a monthly
bucket and follows the 4-cycle process monthly.
The primary step of this process is running a “pre MSR”. This is often done three months prior
where feedback is gathered from regional managers. For example; for December, feedback is
brought three months prior, which is in March. The regional managers share their insights with the
demand planners. Nestle has regions where their total volume is broken down and sent to the 8
regions SKU wise, and decisions regarding each SKU is made, whether or not an SKU performs
better along with the current trend. A monthly number is sent to the regional managers and their
understandings and feedbacks are gathered and taken into consideration. It is analyzed to see if it
has been under forecasted or over forecasted and bottom-up feedback is taken from the regions.
Still, a greater part of the projecting is judgmental and therefore subjective, demand planners make
a base demand estimate which is improved during the Nestlé Sales & operations forecasting
progression with increment (for example; information about promotions) supplied by Sales,
Marketing and Finance. This results in the final demand plan. However, no further developments
in demand forecasting have been made during the last few years in many marketplaces. Most
production is "made to stock", often in huge batches, so while a precise forecast is vital it remains
difficult to accomplish. Forecasts are often on the high side leaving storerooms with redundant
inventory and sales and planners in a discussion about how to close the gap (Armstrong, 2013).
Besides, after gathering all the feedbacks from regionals, a meeting with the respective VU's and
category management is carried out. Here, contemplations are made to see if the regional managers
are sure concerning the decisions taken. If there is a possibility to go for higher numbers, what
implications can be carried out to enable it, and if it is a risk what can be done to remove it,
sometimes gap mitigation is carried out. A follow-up meeting is carried out with the VU's and
ccsd's where possible inputs from the feedbacks are considered. Past months actualization is also
considered, along with the balance to go this year.
After all the clarifications and decisions are made, that document is submitted to the management
accountants. The management accountant works on the numbers, business objectives, and
profitability. The bottom- line and top-line implications according to the forecast given.
When the monthly review is made and management accountants finalize the numbers, the finalized
demand forecast for the next year is made. The 18-month horizon is carried out for 2020, in 2019
September and November, until that the immediate year is mainly focused on. The management
shares their insights and feedback and finalizes the whole demand forecast for that time period.
This is where the forecast is finalized in business operation aspects and handed over to the supply
planners. The supply planners will check if there are any constraints in terms of supply for that
particular forecast. Mitigation plans are made and discussed further at a monthly operation review
to ensure that the forecast build is in a position to be supplied.
This whole process runs every month for all Nestle products; FNP, NNP, and NNN. This process
is carried out at an SKU level. Also, a high-level management review is conducted, and everything
is analyzed at a category level. For example- Nestormalt, in the SKU level will be discussed in 6
SKU but at high-level management, the discussion will be held for the entire category as a whole.
Before carrying out any activity in the future, past data is analyzed and taken into consideration.
The types of promotions conducted, what kind of media activity was used, discussions made to
benefit that SKU, all these data are analyzed and looked in an ROI to verify how effectively that
particular SKU was before and accordingly decide the forecast for the future.
When no historical data is available, for example- if the promotion is carried out for the first time;
demand planners would try to relate it to some event of the same kind which they have carried out
in the past. Through that, a latter understanding is developed. For example- the type of market
share developed and capture, how the consumption can be increased, market share rate, expected
rise in market share if that promotion was carried out. These data are built on hypothesis since no
historical data is properly available; an accurate figure/image about the other external impacts or
causes cannot be identified. So, the assumption is made as such whatever that happened in that
particular month in which the promotion was run remains the same; it is assumed that there is a
high probability of selling the same amount sold in the last year September in next year September
if the same promotion was run.
This is the overall process of how Nestle runs the demand forecasting for all their products on a
monthly bucket, as explained by Mr. Baratha Rathnayaka.
3.2. Unilever
Unilever is a company that mainly produces consumer fast-moving goods (Unilever, 2019). Its
product includes savory, dressings and spread; ice cream and beverages; personal care, and home
care. The company's brands include Axe & Lynx, Blue Band, Dove, Becel & Flora, Heartbrand
ice creams, Hellmann's, Knorr, Lipton, Lux, Omo, Rexona, and Sunsilk. Unilever has three main
product categories (CNN Business, 2019). Personal care products include skin care and hair care
products, deodorants and oral care products. The company Food products include soups, bouillons,
sauces, snacks, mayonnaise, salad dressings, margarine and spreads, and cooking products such as
liquid margarine. Its Refreshment products include ice cream, tea-based beverages, weightmanagement products, and nutritionally enhanced staples sold in developing markets. The
company Home Care products include laundry tablets, powders and liquids, soap bars and a range
of cleaning products (Unilever, 2019).
The demand forecasting process of Unilever is denoted by S&OP which stands for Sales and
Operations Procedure. Unilever examines its demand forecast for 18 individual SKU models by
using specific codes known as base pack codes. When forecasting the demand, Unilever mainly
relies on sales history, mainly 5 years back. Sales are categorized as primary sales and secondary
sales. The primary sale is the process of distributing Unilever products to large scale, around 50 –
60 distributors and secondary sale are when distributors distribute to other distributing channels.
The primary sale is done to the customer and selling to other distributing channels which is known
as the secondary sale. Primary sale can be manipulated, out of these two sales categories, Unilever
believes that the most accurate figures are calculated from the secondary sales numbers.
Forecast methods such as regression analysis, noise clearing methods are also used to predict the
demand. Under this, the deduction of all the anomalies and risks is done to ensure the most accurate
figures are been calculated. For Example, April 2019 was completely unexpected hence it is
regarded as an anomaly and not considered in the trend or future forecasts. Demand planners,
inputs and expectations from the immediate past year's trends are also added to the demand plan.
The least error model from the 18 models tested on is taken into consideration and the base-line
for a product is made.
The demand forecasting process consists of a short-term accurate plan and a three years long term
plan. The short-term plan for the most immediate one year and mainly plans the production
process. The three-year long-term plan consists of the investment details to be made at the right
time, to minimize the capacity constraints and for brand ambitious purposes. A most accurate
forecast is done for the immediate year. Brand ambitions and new product additions for each brand
suggested by brand managers are included in the long-term plan. The one-year plan is monthly
revised and formalized, and the one-month plan is always a frozen plan to align to one fixed
number. The demand forecasting process of Unilever is calculated on a weekly bucket and consists
of the following steps.
Firstly, an activity planning meeting is carried out where the forecast is predicted according to the
trends of past data and inputs from the sales team are taken into consideration. Sales teams' inputs
and expectations are also accommodated to the pure trend, which causes the past trend to go out
of change with reasons. A decision such as whether promotions are needed and other marketing
aspects are brought up in the conduction of this meeting. With the usage of the activity plan and
its inputs, a plan called UDP (Unconstrained Demand Plan) which mainly focuses on the demand
potential, the number of products that can be sold solely on the demand potential is calculated.
Next, the prepared UDP is handed over to the supply planners to receive an idea about whether the
production can be done compared to the capacity available.
Afterward, a meeting with the demand planners and supply planners which is known as DSR
(Demand and Supply Reconciliation) is held to get an idea about the constraints and how to
accommodate the constraints. After conducting the DSR meeting, the DP meeting (Demand
Planning) is held where the brand managers and the trade category teams are also known as the
representatives of sales teams gather up and analyses the information individually. Here, each pack
is examined regarding the trends they process, for any issues or push backs in the forecast, and
insights about the demand and the performance of each product are analyzed.
After preparing a plan according to those accommodated inputs, discussions with the main
category controllers are made regarding the overall category performance, this is conducted at the
S&OP stage. Here, discussions about the growth, expectable position in the market and if there
any issues, suggestions are provided finally formalizing the plan. MCSNOP is the final step of this
process where the formalized plan is aligned with the management committee which includes the
directors in charge of each category, CEOs and high-level management where the forecast is
analyzed according to the main three categories which are Homecare, Personal care, Food Brands.
That is considered as the finalized plan and whole of the Unilever runs upon it. Bottom-up and
top-down are aligned through insights, ambitious and reality must be aligned to form the
formalized final plan.
This is the overall demand forecasting process followed by Unilever as described by Mr. Tharindu
Samaranayake, the Demand Planner Manage of Unilever, Sri Lanka.
4. Critically comment on the application
4.1. Comparing and Contrasting the two companies
It is studied that both Nestle, and Unilever provide products that are essential to the daily lives of
people. Production, packaging, and distribution is carried in a socially friendly manner and all
products are safe to use. Nestle uses around 150-160 small distributors to cover the whole of Sri
Lanka whereas Unilever has around 50 – 60 larger distributors. Either way, both companies make
sure the full market is covered and customers and consumers receive the products on time.
Unilever and Nestle have a rather different products manufactured but the process followed to
forecast the demand is fairly similar. Nestle calculates the forecast for a monthly bucket while
Unilever calculates for a weekly bucket. Unilever consists of one major plan and one minor plan,
the three-year long-term plan is followed to analyses the investments and one-year accurate plan
is made for the immediate year which consists of insights, supply and production plans. Nestle has
an eighteen-month horizon which includes the production and supply followed by the
understandings and insights of their management where everything is finalized. The researchers
of this report believe that Unilever follows a more moderate and accurate plan which ensures that
the sales of its products grow annually and focuses and plans for the future more confidently as
the organization follows three plans in the demand forecasting procedure. It is also clear that
forecasting for a monthly bucket is more accurate which is followed by Nestle while its less
accurate for a weekly bucket followed by Unilever, but when benchmarking, the aggregate of a
weekly bucket is higher than a monthly bucket.
The plan followed by Nestle is the MBP (Multi Business Plan) and Unilever follows an S&OP
plan (Sales and Operations Plan). The processes are fairly the same. The MBP consist of a fourcycle process whereas S&OP has six. The four steps; Pre MSR, Meeting with VU’s and Category
Management, Management accountants meeting and finally the high-level managers, CEOs and
directors meeting. The six steps include; Activity planning, Unconstraint Demand Planning,
Meeting with Supply planners (DSR Meeting), Demand Planning meeting (DP), S&OP meeting
(Sales and Operations Plan) and finally the meeting with category directors and CEOs. It is studied
by the researches that both these plans are strong and accurately forecast the numbers. But, the six-
step cycle is more time consuming whereas the four-step process is much faster and easier to
follow. But both provide accurate results.
Nestle uses accountants managers in the process of demand forecasting unlike in Unilever.
Regardless that, both companies follow the top-down and bottom-up plans. All the high-level
management measures the organization's demand and sales in the top-down view whereas other
levels measure it in a bottom view. Either way, both methods are useful in the demand forecasting
planning procedure.
Unilever and Nestle test their forecast on 18 models. Both organizations consider the most accurate
and least error percentage when calculating the demand. The sales of the most recent year and five
years to the past are considered when analyzing the sales history to forecast the future. It is a
common procedure to remove any old fashion trends and neglect any discontinuing trends in the
demand cycle. If a new trend is seen, both companies add it to the demand trends and adjust the
plans accordingly. If there is a decline in a trend for a particular product, promotion campaigns
and the addition of new features is conducted by both the organizations.
When innovating a new product or running a promotion for the first time, both Nestle, and Unilever
try to match it to any similar product or event in order to create a hypothesis of the possible
outcome of sales.
As studied, it is clear that there are similarities and differences in the procedures followed when
forecasting the demand. Demand planners use similar assumptions and considerations when
analyzing historical data and targets to make the most accurate forecast plan for the time period
forecasted. After all, the end objective of Nestle and Unilever as an organization is to increase the
sales numbers and attract more consumers to the products manufactured hence increasing the
demand for the products which would create higher profits for the organizations.
5. Difficulties, Recommendations and Possible Improvements.
Difficulties faced when planning a forecast is rather similar. Demand forecasting requires high
analysis knowledge and up to date information. Demand planners must be able to identify the
trends and patterns through the analysis of past data and remove any unwanted or old-style trends
from the forecasts.
It was mentioned that forecasting from only past data is a hectic task cause although it is believed
that accurate results can be driven from the past trend, it's not entirely possible to depend on it.
Demand planners must be able to adjust to any emergency and cover up any loses in the company
sales if any cause of an unexpected event occurs. There is no solution for this as the future is always
unpredictable.
Another difficulty mentioned was the acceptance of a product declining by the brand and category
managers. Through the analysis of data for each product, demand planners attempt to suggest if
any product is declining in the market but the product managers at times refuse to admit the
situation. As a solution, managers can invest more in that particular brand and add promotions to
new features to that product which would in return attract more customers and consumers, or else
that product can be replaced by innovation of a similar but more advanced product.
Sudden breakdowns in manufacturing machines was also another issue mentioned. If a cause of
sudden breakdown occurs in the manufacturing plant, supply managers refuse to supply the
forecasted number of products. Hence, this would cause demand planners to unexpectedly reforecast the plan for that particular time period. As a temporary solution, monthly or yearly checks
on the supply machines can be run to ensure the breakdown percentage is at least.
Determining the modern trends and sales in the markets was also mentioned as a difficulty faced
by demand planners. The volatility of the consumer markets changes quite often, and consumers
tend to get attracted to substitute for various reasons. In order to maintain a continuous forecast
number, it is essential to carry out various promotion campaigns, add new features and use natural
ingredients to manufacture the products. The modern society is highly attracted towards herbal,
healthy, nutritious and safe to use products, therefore, it is the responsibility of the supply managers
to take customer recommendations to consideration.
An innovation of a new product is another difficulty faced by demand planners because there is no
historical data available to the demand planners to analyze a forecast. Sales and demand will have
to build on hypothesis and guessing the future trends. As a solution, the organization runs a survey
or could maybe test the product with all types of people. Through the analysis and
recommendations given, a baseline forecast for that product can be made. Demand planners can
also take information from a similar type of product and conduct a comparison.
This same scenario can be followed when an organization is running a promotion for the first time.
Demand planners can compare the event with a similar event conducted by the company and get
a basic idea of how the sales have increased and how the demand was forecasted for that event.
Through the usage of that information, an estimate of the expected forecast can be calculated.
Honest, loyal and trustworthy opinions of stakeholders, supply managers, product and category
managers are also a necessity. For an organization to run smoothly, there has to be proper and
respectful communication methods within the organization. All the organization employees must
be able to adhere to the rules and regulations of the company and unitedly work with each other to
achieve goals and objectives. When all employees work for a common goal, it is much easier for
demand planners to forecast the demand. Adding to that, new innovative ideas can be brought up
and discussed further. Working becomes less stress full and more enjoyable.
Consumer tastes changes and this is quite unpredictable. Customers and consumers would prefer
to try different types of products due to various reasons like boredom of using the same product.
Creating new products and tastes to match customers' and consumers' needs and likes would be
ideal. In order to perform that, the organizations can hire a group of people to study the modern
society and understand the requirements and expectations. Through the consideration of society's
opinions, new innovative products can be manufactured in order to bring satisfaction.
These as studied will positively impact both Unilever and Nestle to grow faster and increase sales
annually. After all, both organizations are leading the economy very well and has grown
throughout the years of business.
6. Conclusion
Demand forecasting methods can vary from organization to organization. But, the end result and
goal of an organization is the same. To increase sales globally and locally, to provide the best
products and satisfy the needs and wants of people are common goals to be achieved. In order to
achieve these goals, companies should make sure that their demand forecasting is done properly
since demand forecasting helps the companies to plan and schedule production, acquire to make
provisions for finances, formulating price strategy, for promotional advertisements, etc. Moreover,
demand forecasting can be done in two different ways which are short term and long term
forecasting and also consists of three levels such as macro, micro, and industry level forecasting.
Nestle follows the Multi Business Plan (MBP) and has a long-term plan of 18 months and a
monthly bucket forecast whereas Unilever follows a Sales and Operations Procedure (S&OP)
consisting of a 3-year long term plan, 1-year accurate plan, and a weekly bucket forecast. The
MBP consist of a four-cycle process whereas S&OP has six. The Pre MSR, Meeting with VU’s
and Category Management, Management accountants meeting and finally the high-level
managers, CEOs and directors meeting are the steps followed by Nestle whereas Unilever follows
six steps which include; Activity planning, Unconstraint Demand Planning, Meeting with Supply
planners (DSR Meeting), Demand Planning meeting (DP), S&OP meeting (Sales and Operations
Plan) and finally the meeting with category directors and CEOs.
Similarly, demand planners of both the organizations suggest that an accurate forecast can be
calculated through the analysis of historical data, but it is somewhat unreliable when unexpected
situations occur, regardless that all future forecasts are made with the usage of past sales. It is quite
unpredictable how consumer taste can change, but when making the plan, the newest trends are
added, and the forecast is varied accordingly.
Product knowledge, proper knowledge about the customers, knowledge about the environment can
be considered as the requirements to do an accurate demand forecasting process. Further, when
considering Nestle and Unilever, accuracy, plausibility, durability, flexibility, availability of data,
cost, and managerial effort, simplicity, consistency can be identified as characteristics of a good
forecasting method. Overall, considering both the organizations, it is possible to conclude that
demand forecasting is a necessity and an important role to adhere in a company. If not for an
accurate forecast, the possibility of a company to increase sales or run the business is impossible.
Hence, it is the responsibility of the demand planners to fully focus on the forecast calculated and
make sure it is the most accurate plan with the least errors possible.
7. Referencing
Armstrong, H. (2013) Supply Chain Movement. Available at:
https://www.supplychainmovement.com/andreas-gartner-of-nestle-on-forecasting-track-the-madbulls/ (Accessed: 16th November 2019.
Anaplan (2019) Demand Planners Beginners Guide. Available
at: https://www.anaplan.com/blog/demand-planning-fundamentals-and-futures/ (Accessed: 16th
November 2019)
CNN Business (2019) Nestle SA. Available
at:https://money.cnn.com/quote/profile/profile.html?symb=NSRGY (Accessed: 18th November
2019)
CNN Business (2019) Unilever PLC. Available at:
https://money.cnn.com/quote/profile/profile.html?symb=UL (Accessed: 18th November 2019)
Nestle (2019) Nestle; Good Food, Good Life. Available at: https://www.nestle.com/aboutus
(Accessed: 16th November 2019).
Nitisha (no date) Demand Forecasting: Concept, Objectives, and Factors. Available
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