UNIT – 1

Generation and Screening of a project idea

Generation and Screening of a project idea begins when someone with specialized knowledge or expertise
or some other competence feels that he can offer a product or service

♦ Which can cater to a presently unmet need and demand

♦ To serve a market where demand exceeds supply

♦ Which can effectively compete with similar products or services due to its better quality/price etc.

An organization has to identify investment opportunities which are feasible and promising before taking a
full fledged project analysis to know which projects merit further examination and appraisal.

Generation and Screening of a project idea involves the following tasks :-

(1) Generation of ideas –

A panel is formed for the purpose of identifying investment opportunities. It involves the
following tasks which must be carried out in order to come up with a creative idea
–

(a) SWOT analysis – Identifying opportunities that can be profitably exploited

(b) Determination of objectives – Setting up operational objectives like cost reduction,

productivity improvement, increase in capacity utilization, improvement in contribution margin

(c) Creating Good environment – A good organizational atmosphere motivates employees to be

more creative and encourages techniques like brainstorming, group discussion etc. which results
in development of creative and innovative ideas.

(2) Monitoring the Environment –

An Organization should systematically monitor the environment and assess its competitive abilities in
order to profitably exploit opportunities present in the environment. The key sectors of the environment
that are to be studied are :-

(a) Economic Sector – It includes, State of economy, Overall rate of Growth, Growth of primary,
secondary and tertiary sectors, Inflation rate, Linkage with world economy, BOP situation, Trade
Surplus/Deficit.

(b) Government Sector –

It includes, Industrial policy, Government programmes and projects, Tax framework, Subsidies,
incentives, concessions, Import and export policies, Financing norms.
(c) Technological Sector – It includes, State of technology, Emergence of new technology, Receptiveness
of the industry, Access to technical know how.

(d) Socio-demographic sector – It Includes, Population trends, Income distribution, Educational profile,
Employment of women, Attitude towards consumption and investment.

(e) Competition Sector – It includes, No. of firms and their market share, Degree of homogeneity and
production differentiation, Entry barriers, Marketing policies and prices, Comparison with substitutes
in terms of quality/price/appeal etc.

(f) Supplier Sector – Availability and cost of raw material, energy and money

(3) Corporate Appraisal –

It involves identification of corporate strengths and weaknesses. The important aspects that are to be
considered are:-

(a) Market and Distribution –

i. Market Image
ii. Market share
iii. Marketing and Distribution cost
iv. Product line
v. Distribution Network
vi. Customer loyalty

(b) Production and Operations –

i. Condition and capacity of plant and machinery
ii. Availability of raw materials and power
iii. Degree of vertical integration
iv. Location advantage
v. Cost structure – Fixed and Variable costs

(c) Research and Development –

i. Research capabilities of a firm
ii. Track record of new product developments
iii. Laboratories and testing facilities
iv. Coordination between research and other departments of the organization

(d) Corporate Resources and Personnel –

i. Corporate Image
ii. Clout with government and regulatory agencies
iii. Dynamism of top management
iv. Competence and commitment of employees
v. State of industrial relations
(e) Finance and Accounting –
i. Financial leverage and borrowing capacity
ii. Cost of capital
iii. Tax situation
iv. Relations with shareholders and creditors
v. Accounting and control system
vi. Cash flows and liquidity

Tools for identifying investment opportunities →

(a) Porter 5 forces Model → It helps in analyzing profit potential of an industry depending upon strength
of –
i. Threat of new entrants
ii. Rivalry amongst existing companies
iii. Pressure from substitute products
iv. Bargaining power of buyer
v. Bargaining power of seller

(b) Life cycle Approach → There are four stages a product goes through during his life cycle each stage
represents different investment and net profit value →

(a) Pioneering Stage – In this stage the technology and product is new, there is high competition and
very few entrants survive this stage.
(b) Rapid Growth Stage – This stage witnesses a significant expansion in sales and profit.
(c) Maturity Stage – It marks developed industries with mature product and steady growth rate.
(d) Decline Stage – Due to introduction of new products and changes in customer preference the
industry incurs a decline in market share and profits.
(c) Experience Curve → Experience curve analyzes how cost per unit changes with respect to
accumulated volume of production. Investment must be such that reduces costs.

(4) Looking for Project Ideas –

Various sources to look for good project ideas include:-

i. Trade fairs and exhibitions
ii. Studying Government plans and guidelines
iii. Suggestion of financial institutions and development agencies
iv. Investigating local materials and resources
v. Analyzing performance of existing industries
vi. Analyzing social and economic trends
vii. Analyzing new technological developments
viii. Studying the consumption pattern of people abroad
ix. Stimulating creativity to produce new ideas
x. Reducing exports and imports

(5) Preliminary Screening –

It refers to elimination of project ideas which are not promising. The factors to be considered while
screening for ideas are:-
♦ Compatibility with the promoter – The idea must be consistent with the interest, personality and
resources of entrepreneur.
♦ Consistency with Government priorities – The idea must be feasible with national goals and
government regulations.
♦ Availability of inputs – Availability of power, raw material, capital requirements, technology.
♦ Adequacy of Market – Growth in market, prospect of adequate sale, reasonable Return on Investment.
♦ Reasonableness of cost – The project must be able to make reasonable profits with respect to the costs
involved.
♦ Acceptability of risk level – The desirability of the project also depends upon risks involved in
executing it. In order to access risk the following factors must be considered:-
-Project`s vulnerability to business cycles
-Change technology
-Competition from substitutes
-Government`s control over price and distribution
-Competition from imports

(6) Project Rating Index →

It is a tool used for evaluating large number of project ideas. It helps in streamlining the process of
preliminary screening. Hence a preliminary evaluation may be converted in project rating index.
Steps to calculate project rating index→

I. Identifying the factors relevant for project rating

II. Assigning weights to these factors according to their relative importance(FW)

III. Rate the project proposal on various factors using suitable rating scale (FR) (5 point scale or 7
point scale)

IV. For each factor multiply the factor rating with factor weight to get factor scores (FR X FW = FS)
V. All the factor scores are added to get the overall project rating index. Organization determines a cut
off value and the project below this cut off value are rejected.

(7) Sources of the Net Present Value

In order to select a profitable and feasible project, a project manager must carry out a fundamental
analysis of the product and factor market to know about entry barriers which lead to positive net present
value. There are six entry barriers which result in a positive NPV project. They are –
i. Economies of scale
ii. Product differentiation
iii. Cost advantage
iv. Marketing reach
v. Technological edge
vi. Government policy
 ENTREPRENEURIAL SKILLS

Entrepreneur skills include various skill sets such as

leadership, business management, time management,
creative thinking and problem-solving. You can apply these
skills in many job roles and industries. These entrepreneur
skills are vital for promoting innovation, business growth and
competitiveness. Developing these skills means developing
many skills together. For example, to be a successful
entrepreneur, you may need to develop your risk-taking skills
and sharpen your business management skills.
BUSINESS MANAGEMENT SKILLS
Business management skills are traits an entrepreneur must
have to run a business and ensure all business goals are met.
Entrepreneurs with this skill set can oversee and manage
operations of different departments because they possess a
good understanding of each function. Business management
skills include multitasking, delegating responsibilities and
making critical business decisions.

COMMUNICATION AND ACTIVE LISTENING SKILLS

Every entrepreneur must be able to communicate effectively
with clients, team members and all other stakeholders.
Whether through verbal communication during meetings or
sending reports and messages through emails about the
project, entrepreneurs require superior written and verbal
communication. Apart from communication skills,
entrepreneurs must be excellent listeners to understand the
project's requirement and discussion during project meetings.

RISK TAKING SKILLS

Being able to take calculated and intelligent risks is one of the
essential entrepreneur skills to learn. Employees with an
entrepreneur mindset never shy away from taking risks
because they understand that calculated risks result in
tremendous success. They know that risk is an opportunity to
learn and grow a business to the next level. Employers want
candidates who can take risks in pursuit of potential gains and
profit.

NETWORKING SKILLS
Networking involves building and managing relationship with
other professionals to grow and promote a business. Effective
networking skills open up future opportunities and help build a
solid brand. Networking allows entrepreneurs to meet like-
minded professionals, build future teams and stay up-to-date
with industry trends. It is one of the most desirable skills for
entrepreneurs because, through a solid network, they can
meet professionals to fund their ideas, access professional
business expertise and get feedback on their new venture or
idea.

CRITICAL THINKING SKILLS

Critical thinking is an entrepreneur skill that objectively
analyses the information and draws a rational conclusion. It
helps entrepreneurs assess a situation and come up with a
logical solution. Employers look for candidates with critical
thinking because it helps solve problems and build strategies
for business growth. Usually, a critical thinker is independent,
competent and reflective. This skill helps entrepreneurs
logically connect ideas, scrutinise information, evaluate
arguments, find inconsistencies in work and solve complex
issues. Instead of memorising information, such candidates
use the information to deduce meaningful insights.

PROBLEM SOLVING SKILLS

Often, entrepreneurs face challenging and unexpected
situations. It could be a venture capitalist refusing further
funding or a team member refusing to work as per the project
guidelines; an entrepreneur must possess excellent problem-
solving skills to handle stressful situations and calmly identify
alternate solutions. Exceptional problem-solving skills ensure
they reach their business goal.

CREATIVE THINKING SKILLS

Creativity is a valuable yet underappreciated skill in the digital
world. Creative thinking is the backbone for innovation and it
forces employees to think differently. Entrepreneurs with
creative thinking skills are never hesitant to try solutions that
others may overlook because of fear of failure. Such people
think out-of-the-box and always seek input from professionals
in a different field for understanding a new perspective. It is
one of the most sought-after entrepreneur skills because it
allows them to see patterns (even when there are no patterns)
and develop innovative ways to solve business issues.

CUSTOMER SERVICE SKILLS

Quality customer service promotes the brand and increases
loyalty. Regardless of the industry, excellent customer service
skills are essential for business success. From talking to
clients to discussing funding opportunities, customer service
skills help entrepreneurs connect with their potential
customers.

FINANCIAL SKILLS
The ability to handle resources, assess investments, calculate
ROI is a must for entrepreneurs. Apart from this, they must
know how to use accounting and budgeting software to keep
track of all the financial processes. By learning financial skills,
entrepreneurs avoid overspending and optimally allocate
resources.

LEADERSHIP SKILLS
Being able to inspire colleagues, empower the workforce and
lead from the front requires excellent leadership skills.
Exemplary leaders lead by examples and can take a
leadership role and work as a part of a team. Entrepreneurs
with leadership skills motivate their employees, manage
operations and delegate tasks to reach the business goal.
TIME MANAGEMENT AND ORGANISATIONAL SKILLS
Effective time management increases productivity and
organises your workspace. Entrepreneurs with time
management and organisational skills understand different
ways to prioritise tasks and avoid procrastination. For
ensuring timely completion of projects, entrepreneurs analyse
their and their team's time, set time limit for each task,
complete priority tasks first, delegate work to others, create a
to-do list and use technology to keep the workspace
organised.
TECHNICAL SKILLS
Technical skills are hard skills that are gained by using digital
tools and software. Entrepreneurs must know how to use
planning, marketing and budgeting software. Knowledge of
software helps in managing projects, tracking sales and
allocating a viable budget for the project.

HOW TO IMPROVE ENTREPRENEUR SKILLS

Mastery of these entrepreneur skills can help you outperform

at your job and steer your business to success. To improve
your skills, you may read books, take a course or attend
seminars. Here are some steps you must follow to improve
your entrepreneur skills:

1. READ BUSINESS BOOKS

Reading books encourages self-improvement and is an
excellent way to get advice on effective business
strategies. It improve your cognitive ability, increases your
decision-making and you get to learn from the failure of
others. Therefore, read books to achieve success as an
entrepreneur.
2. ENROL IN A COURSE
Another way to sharpen your skill set is by enrolling in a
management, marketing or finance course. Taking and
 completing a professional course may help boost your
business management and financial planning skills.
3. ATTEND WORKSHOPS
Always attend entrepreneurial workshops and networking
events. Many of these workshops may have experienced
business owners as speakers. It helps fill the knowledge
gap and you may gain valuable insights on how to run your
business to success. Such workshops are a great way to
build networks and talk with industry leaders.
4. LISTEN TO PODCASTS
One of the best ways to consume business-related
information on a busy day is listening to a podcast of
successful entrepreneurs. Listening to business podcasts
may give you insights into how different entrepreneurs use
technology to speed up their business growth. It also
improves your listening skills.
5. HIRE AN EXPERIENCED BUSINESS MENTOR
Experienced mentors can help you develop the skills that
you are lacking. You can either work under a successful
business owner for some time to understand how to
manage a business. You can also meet up regularly with a
professional group of like-minded people and discuss
different ways of building and marketing a brand. Mentors
help in providing valuable insights and professional advice
that is necessary for success.

An individual must possess the following traits and qualities in order to be a successful entrepreneur –
i. He must be Willing to make sacrifices
ii. He must be a good Leader
iii. He must be able to make quick and rational decisions
iv. He must have confidence in the project
v. He must able to exploit market opportunities
vi. He must have strong ego in order to survive ups and downs of a business.

MARKET AND DEMAND ANALYSIS

In most cases, the first step in project analysis is to estimate the potential size of the market for the product
proposed to be manufactured (or service planned to b offered) and get an idea about the market share that is
likely to be captured. Put differently, market and demand analysis is concerned with two broad issues:

1) What is the likely aggregate demand for the product/service?

2) What share of the market will the proposed project enjoy?

Given the importance of market and demand analysis, it should be carried-out in an orderly and systematic
manner:

1) Situational analysis and specification of objectives,

2) Collection of secondary information,
3) Conduct of market survey,
4) Characterization of the market,
5) Demand forecasting,
6) Market planning.

1) Situational Analysis and Specification of Objectives: In order to get a “feel” of the relationship
between the product and its market, the project may informally talk to customers, competitors, middlemen,
and others in the industry. Wherever possible, h may look at the experience of the company to learn about
the performances and purchasing power of customers, actions and strategies of competitors and practices of
the middlemen.

If such a situational analysis generates enough data to measure the market and get a reliable handle over
projected demand and revenues, a formal study need not be carried- out, particularly when cost and time
considerations so suggest.

2) Collection of Secondary Information: Secondary information is the information that has been gathered
in some other context and is already available. Primary information, on the other hand, represents
information that is collected for the first time to meet the specific purpose on hand. Secondary information
provides the base and the starting point for the market analysis.

General Sources of Secondary Information

i) Census of India,
ii) National sample survey reports,
iii) Plan reports,
iv) Statistical abstract of the Indian union,
v) India year book,
vi) Statistical year book,
vii) Economic survey of industries,
viii) Annual survey of industries,
ix) Annual reports of the development wing, Ministry of Commerce and Industry, etc.

3) Conduct of Market Survey: Secondary information, though useful, often does not provide a
comprehensive basis for market and demand analysis. It needs to be supplemented with primary information
gathered through a market survey, specific to the project being appraised.

The market survey may be census survey or a sample survey. In a census survey, the entire population is
covered. The word ‘population’ is used here in a particular sense. It refers to the totality of all units under
consideration in a specific study.

The market survey, in practice, is typically a sample survey. In such a survey a sample of population is
contacted or observed and relevant information is gathered. On the basis of such information, inferences
about the population may be drawn.

The information sought in a market survey may relate to one or more of the following:
i) Total demand and rate of growth of demand,
ii) Demand in different segments of the market,
iii) Income and price elasticities of demand,
iv) Motives for buying,
v) Purchasing plans and intentions,
vi) Satisfaction with existing products,
vii) Unsatisfied needs,
viii) Attitudes toward various products,
ix) Distributive trade practices and preferences,
x) Socio-economic characteristics of buyers.

4) Characterization of the Market: Based on the information gathered from secondary sources and
through the market survey, the market for the product/ service may be described in terms of the following:

i) Effective Demand in the Past and Present: To gauge the effective demand in the past and present, the
starting point typically is apparent consumption which is deemed as:

Production + Imports - Exports - Changes in stock level

The figure of apparent consumption has to be adjusted for consumption of the product by the producers and
the effect of abnormal factors. The consumption series, after such adjustments, may be obtained for several
years.

ii) Break-down of Demand: To get a deeper insight into the nature of demand, the aggregate (total) market
demand may be broken-down into demand for different segments of the market. Market segments may be
defined by:
a) Nature of product.
b) Consumer group, and
c) Geographical division.

iii) Price: Price statics must be gathered along with statistics pertaining to physical quantities. It may be
helpful to distinguish the following types of prices.
a) Manufacturer’s price quoted as FOB (Free on Board) price or CIF (Cost, Insurance and Freight) price,
b) Landed price for imported goods,
c) Average wholesale price and
d) Average retail price.

iv) Methods of Distribution and Sales Promotion: The method of distribution may vary with the nature of
the product. Capital goods, industrial raw materials or intermediates and consumer products tend to have
different distribution channels. Likewise, methods used for sales promotion (advertising, discounts, gift
schemes, etc.) may vary from product to product.

v) Consumers: Consumers may be characterized along two dimensions as follows:

Demographic and Sociological Attitudinal
Age Preferences
Sex Intentions
Income Habits
Profession Attitudes
Residence Responses
Social background

vi) Supply and Competition: It is necessary to know the existing sources of supply and whether they are
foreign or domestic. For domestic sources of supply, information along the following lines may be gathered;
a) Location,
b) Present production capacity,
c) Planned expansion,
d) Capacity utilization level,
e) Bottlenecks in production and
f) Cost structure.

Competition from substitutes and near-substitutes should be specified because almost any product may be
replaced by some other product as a result of relative changes in price, quality, availability, promotional
effort and so on.

vii) Government policy: Thee role of the government in influencing the demand and market for a product
may be significant. Governmental plans, policies, and legislations, which have a bearing on the market and
demand of the product under examination, should be spell-out. These are reflected in:
a) Production targets in national plans,
b) Import and export trade controls,
c) Import duties,
d) Export incentives,
e) Excise duties,
f) Sales tax,
g) Industrial licensing,
h) Preferential purchases,
i) Credit controls, financial regulations and
j) Subsides/ penalties of various kinds.

5) Demand Forecasting: On the basis of analysis and interpretation of information gathered about various
aspects of market and demand from primary and secondary sources, an attempt is made to forecast the
future demand of the proposed product or service. There are various methods of demand forecasting
available to the market analyst.

Methods of Demand Analysis

The various methods of forecasting demand may be grouped under the following categories:

1) Opinion Polling Method: In this method, the opinion of the buyers, sales force and experts could be
gathered to determine the emerging trend in the market. The opinion polling methods of demand forecasting
are of three kinds:
i) Consumers Survey Methods: The most direct method of forecasting demand in the short-run is survey
method. Surveys are conducted to collect information about future purchase plans of the probable buyers of
the product. Survey methods include:

a) Complete Enumeration Survey: Under the Complete Enumeration Survey, the firm has to go for a door to
door survey for the forecast period by contacting all the households in the area.

b) Sample Survey and Test Marketing: Under this method some representative households are selected on
random basis as samples and their opinion is taken as the generalized opinion. This method on random basis
as samples and their opinion is taken as the generalized opinion. This method is based on the basic
assumption that the sample truly represents the population. A variant of sample survey technique is test
marketing. Product testing essentially involves placing the product with a number of users for a set period.
Their reactions to the product are noted after a period of time and an estimate of likely demand is mad from
the result.

c)(i) End–use Method: In this method, the sale of the product under consideration is projecting on the basis
of demand survey of the industries using this product and intermediate product. In other words, demand for
the final product is the end use demand of the intermediate product used in the production of this final
product.
ii) Sales Force Opinion Method: This is also known as Collective Opinion Method. In this method, instead
of consumers, the opinion of the salesman is sought. It is sometimes referred as the “grass roots approach”
as it is a bottom-up method that requires each sales person in the company to make an individual forecast
for his or her particular sales territory. These individual forecasts are discussed and agreed with the sales
manager. The composite of all forecasts then constitutes the sales forecast for the organization.

iii) Delphi Method: This method is also known as Expert opinion method of investigation. In this method
instead of depending upon the opinions of buyers and salesmen, firms can obtain views of the specialists or
experts in their respective fields. Opinions of different experts are sought and their identity is kept secret.

These opinions are then exchanged among the various experts and their reactions are sought and analyzed.
The process goes on until some sort of unanimity is arrived at among all the experts. This method is best
suited in circumstances where intractable changes are occurring.

2) Statistical or Analytical Methods: Statistical methods are considered to be superior techniques of demand
estimation because:
i) The element of subjectivity in this method is minimum,
ii) Method of estimation is scientific,
iii) Estimation is based on the theoretical relationship between the dependents and independents variables,
iv) Estimates are relatively more reliable and
v) Estimation involves smaller cost.

The statistical methods, which are frequently used, for making demand projections are:

i) Thread Projection Method: An old firm can use its data of past years regarding its sales in past years.
These data are known as time series of sales. A trend line can be fitted by graphic method or by algebraic
equations. Equations method is more appropriate. The trend can be estimated by using any one of the
following methods.
a) Graphical Method: A trend line can be fitted through a series graphically. Old values of sales for different
areas are plotted on a graph and a free hand curve is drawn passing through as many points as possible. The
direction of this free hand curve shows the trend. The main draw back of this method is that it may show the
trend but not measure it.
b) Least Square Method: The least square method is based on the assumption that the past rate of change of
the variable under study will continue in the future. It is a mathematical procedure for fitting a line to a set
of observed data points in such a manner that the sum of the squared difference between the calculated and
observed value is minimized. This technique is used to find a trend line which best fit the available data.
The trend is then used to project department variable in the future. This method is very popular because it is
simple and in expensive.
c) Time Series Methods: Time series forecasting methods are based on analysis of historical data (time
series; a set of observations measured at successive times or over successive periods). They make the
assumption that past patterns in data can be used to forecast future data points.

Moving averages (simple moving average, weighed moving average); forecast is based on arithmetic
average of a given number of past data points.

Components of Time series Demand

• Average: The mean of the observations over time.
• Trend: A gradual increase or decrease in the average over time.
• Seasonal Influence: Predictable short-term cycling behavior due to time of day, week, month, season, year,
etc.
• Cyclical Movement: Unpredictable long-term cycling behavior due to business cycle or product/service
life cycle.
• Random Error: Remaining variation that cannot be explained by the other four components.

d) Exponential Smoothing: It is one of the methods of trend projection methods. Exponential smoothing is
distinguishable by the special way it weights ach past demand. The pattern of weights is exponential in
form. Demand for the most recent period is weighted most heavily; the weights placed on successively older
periods decrease exponentially. In other words , the weights decrease in magnitude the future back in time
the data are weighted ; the decrease is non-linear (exponential).
ii) Regression method: This is a very common method of forecasting demand. Under this method a
relationship is established between quantity demanded (dependent variable) and independent variables such
as income, price of the good, prices of the related goods etc. Once the relationship is established, we drive
regression equation assuming relationship between dependent and independent variables. Once the
regression equation is derived the value of Y i.e. quantity demanded can be estimated for any given value of
X.

iii) Simultaneous equations Methods of Forecasting: The econometric model forecasting involves
estimating several simultaneous equations, which are, generally, behavioral equations, mathematical
identities and market-clearing equations.

The econometric model technique is also known as simultaneous equations method and complete system
approach to forecasting. This technique uses sophisticated mathematical and statistical tools.

iv) Barometric Method: It is also known as ‘leading indicators forecasting’. National bureau of Economic
Research of U.S.A. has identified three types of indicators, coincidental indicators and Lagging indicators.

The analyst should establish relationship between the sales of the product and the economic indicators to
project the correct sales and to measure to what extent these indicators affect the sales. To establish
relationship is not easy task especially in case of new product where there is no past record.

6) Market Planning: The market plans usually have the following components:

i) Current Marketing Situation: This part of the marketing plan deals with the different dimensions of the
current situation. It examines the market situation, competitive situation, distribution situation and the
macro-environment. In other words, it paints a pen-picture of the present.

ii) Opportunity and Issue Analysis: In this section a SWOT (Strength, Weakness, Opportunity, Threat
Analysis) is conducted for Alpha and the core issues before the product are identified.

iii) Objectives: Objectives have to be clear cut, specific and achievable.

iv) Marketing Strategy: The marketing strategy covers the following: target segment, positioning, product
line, price, distribution, sales force, sales promotion and advertising.

v) Action Programme: The last component of market planning is the action programme. Action programmes
operationalize the strategy.

COLLECTION OF PRIMARY AND SECONDARY DATA

In a time when data is becoming easily accessible to researchers all over the world, the practicality of utilizing
secondary data for research is becoming more prevalent, same as its questionable authenticity when compared with
primary data.

These 2 types of data, when considered for research is a double-edged sword because it can equally make a research
project as well as it can mar it.

In a nutshell, primary data and secondary data both have their advantages and disadvantages. Therefore, when carrying
out research, it is left for the researcher to weigh these factors and choose the better one.

It is therefore important for one to study the similarities and differences between these data types so as to make proper
decisions when choosing a better data type for research work.
 What is Primary Data?

Primary data is the kind of data that is collected directly from the data source without going through any existing
sources. It is mostly collected specially for a research project and may be shared publicly to be used for other research

Primary data is often reliable, authentic, and objective in as much as it was collected with the purpose of addressing a
particular research problem. It is noteworthy that primary data is not commonly collected because of the high cost of
implementation.

A common example of primary data is the data collected by organizations during market research, product research,
and competitive analysis. This data is collected directly from its original source which in most cases are the existing
and potential customers.

Most of the people who collect primary data are government authorized agencies, investigators, research-based private
institutions, etc.

Pros

 Primary data is specific to the needs of the researcher at the moment of data collection. The researcher is able
to control the kind of data that is being collected.
 It is accurate compared to secondary data. The data is not subjected to personal bias and as such the
authenticity can be trusted.
 The researcher exhibit ownership of the data collected through primary research. He or she may choose to
make it available publicly, patent it, or even sell it.
 Primary data is usually up to date because it collects data in real-time and does not collect data from old
sources.
 The researcher has full control over the data collected through primary research. He can decide which design,
method, and data analysis techniques to be used.

Cons

 Primary data is very expensive compared to secondary data. Therefore, it might be difficult to collect primary
data.
 It is time-consuming.
 It may not be feasible to collect primary data in some cases due to its complexity and required commitment.

What is Secondary Data?

Secondary data is the data that has been collected in the past by someone else but made available for others to use.
They are usually once primary data but become secondary when used by a third party.

Secondary data are usually easily accessible to researchers and individuals because they are mostly shared publicly.
This, however, means that the data are usually general and not tailored specifically to meet the researcher's needs as
primary data does.

For example, when conducting a research thesis, researchers need to consult past works done in this field and add
findings to the literature review. Some other things like definitions and theorems are secondary data that are added to
the thesis to be properly referenced and cited accordingly.

Some common sources of secondary data include trade publications, government statistics, journals, etc. In most cases,
these sources cannot be trusted as authentic.

Pros

 Secondary data is easily accessible compared to primary data. Secondary data is available on different
platforms that can be accessed by the researcher.
  Secondary data is very affordable. It requires little to no cost to acquire them because they are sometimes
given out for free.
 The time spent on collecting secondary data is usually very little compared to that of primary data.
 Secondary data makes it possible to carry out longitudinal studies without having to wait for a long time to
draw conclusions.
 It helps to generate new insights into existing primary data.

Cons

 Secondary data may not be authentic and reliable. A researcher may need to further verify the data collected
from the available sources.
 Researchers may have to deal with irrelevant data before finally finding the required data.
 Some of the data is exaggerated due to the personal bias of the data source.
 Secondary data sources are sometimes outdated with no new data to replace the old ones.

Here are 15 differences between primary and secondary data

 Definition

Primary data is the type of data that is collected by researchers directly from main sources while secondary data is the
data that has already been collected through primary sources and made readily available for researchers to use for
their own research.

The main difference between these 2 definitions is the fact that primary data is collected from the main source of data,
while secondary data is not.

The secondary data made available to researchers from existing sources are formerly primary data that was collected
for research in the past. The availability of secondary data is highly dependent on the primary researcher's decision to
share their data publicly or not.

 Examples:

An example of primary data is the national census data collected by the government while an example of secondary
data is the data collected from online sources. The secondary data collected from an online source could be the primary
data collected by another researcher.

For example, the government, after successfully the national census, share the results in newspapers, online magazines,
press releases, etc. Another government agency that is trying to allocate the state budget for healthcare, education, etc.
may need to access the census results.

With access to this information, the number of children who needs education can be analyzed and hard to determine
the amount that should be allocated to the education sector. Similarly, knowing the number of old people will help in
allocating funds for them in the health sector.

 Data Types

The type of data provided by primary data is real-time, while the data provided by secondary data is stale.
Researchers are able to have access to the most recent data when conducting primary research, which may not be the
case for secondary data.

Secondary data have to depend on primary data that has been collected in the past to perform research. In some cases,
the researcher may be lucky that the data is collected close to the time that he or she is conducting research.

Therefore, reducing the amount of difference between the secondary data being used and the recent data.

 Process
Researchers are usually very involved in the primary data collection process, while secondary data is quick and
easy to collect. This is due to the fact that primary research is mostly longitudinal.

Therefore, researchers have to spend a long time performing research, recording information, and analyzing the data.
This data can be collected and analyzed within a few hours when conducting secondary research.

For example, an organization may spend a long time analyzing the market size for transport companies looking to talk
into the ride-hailing sector. A potential investor will take this data and use it to inform his decision of investing in the
sector or not.

 Availability

Primary data is available in crude form while secondary data is available in a refined form. That is, secondary data is
usually made available to the public in a simple form for a layman to understand while primary data are usually raw
and will have to be simplified by the researcher.

Secondary data are this way because they have previously been broken down by researchers who collected the primary
data afresh. A good example is the Thomson Reuters annual market reports that are made available to the public.

When Thomson Reuters collect this data afresh, they are usually raw and may be difficult to understand. They simplify
the results of this data by visualizing it with graphs, charts, and explanations in words.

 Data Collection Tools

Primary data can be collected using surveys and questionnaires while secondary data are collected using the
library, bots, etc. The different ones between these data collection tools are glaring and can it be interchangeably
used.

When collecting primary data, researchers lookout for a tool that can be easily used and can collect reliable data. One
of the best primary data collection tools that satisfy this condition is Formplus.

Formplus is a web-based primary data collection tool that helps researchers collect reliable data while simultaneously
increasing the response rate from respondents.

 Sources

Primary data sources include; Surveys, observations, experiments, questionnaires, focus groups, interviews, etc.,
while secondary data sources include; books, journals, articles, web pages, blogs, etc. These sources vary explicitly
and there is no intersection between the primary and secondary data sources.

Primary data sources are sources that require a deep commitment from researchers and require interaction with the
subject of study. Secondary data, on the other hand, do not require interaction with the subject of study before it can be
collected.

In most cases, secondary researchers do not have any interaction with the subject of research.

 Specific

Primary data is always specific to the researcher's needs, while secondary data may or may not be specific to the
researcher's needs. It depends solely on the kind of data the researcher was able to lay hands on.

Secondary researchers may be lucky to have access to data tailored specifically to meet their needs, which mag is not
the case in some cases. For example, a market researcher researching the purchasing power of people from a particular
community may not have access to the data of the subject community.
Alternatively, there may be another community with a similar standard of living to the subject community whose data
is available. The researcher mag uses to settle for this data and use it to inform his conclusion on the subject
community.

 Advantage

Some common advantages of primary data are its authenticity, specific nature, and up to date information while
secondary data is very cheap and not time-consuming.

Primary data is very reliable because it is usually objective and collected directly from the original source. It also gives
up-to-date information about a research topic compared to secondary data.

Secondary day, on the other hand, is not expensive making it easy for people to conduct secondary research. It doesn't
take so much time and most of the secondary data sources can be accessed for free.

 Disadvantage

The disadvantage of primary data is the cost and time spent on data collection while secondary data may be
outdated or irrelevant. Primary data incur so much cost and takes time because of the processes involved in carrying
out primary research.

For example, when physically interviewing research subjects, one may need one or more professionals, including the
interviewees, videographers who will make a record of the interview in some cases and the people involved in
preparing for the interview. Apart from the time required, the cost of doing this may be relatively high.

Secondary data may be outdated and irrelevant. In fact, researchers have to surf through irrelevant data before finally
having access to the data relevant to the research purpose.

 Accuracy and Reliability

Primary data is more accurate and reliable while secondary data is relatively less reliable and accurate. This is
mainly because the secondary data sources are not regulated and are subject to personal bias.

A good example of this is business owners who lay bloggers to write good reviews about their product just to gain
more customers. This is not the case with primary data which is collected by being a researcher himself.

One of the researcher's aims when gathering primary data for research will be gathering accurate data so as to arrive at
correct conclusions. Therefore, biases will be avoided at all costs (e.g. same businesses when collecting feedback from
customers).

 Cost-effectiveness

Primary data is very expensive while secondary data is economical. When working on a low budget, it is better for
researchers to work with secondary data, then analyze it to uncover new trends.

In fact, a researcher might work with both primary data and secondary data for one research. This is usually very
advisable in cases whereby the available secondary data does not fully meet the research needs.

Therefore, a little extension on the available data will be done and cost will also be saved. For example, a researcher
may require a market report from 2010 to 2019 while the available reports stop at 2018.

 Collection Time

The time required to collect primary data is usually long while that required to collect secondary data is usually short.
The primary data collection process is sometimes longitudinal in nature.
Therefore, researchers may need to observe the research subject for some time while taking down important data. For
example, when observing the behavior of a group of people or particular species, researchers have to observe them for
a while.

Secondary data can, however, be collected in a matter of minutes and analyzed to dead conclusions—taking a shorter
time when compared to primary data. In some rare cases, especially when collecting little data, secondary data may
take a longer time because of difficulty consulting different data sources to find the right data.

Similarities Between Primary & Secondary Data

 Contains Same Content:

Secondary data was once primary data when it was newly collected by the first researcher. The content of the data
collected does not change and therefore has the same content as primary data.

It doesn't matter if it was further visualized in the secondary form, the content does not change. A common example of
these are definitions, theorems, and postulates that were made years ago but still remain the same.

 Uses

Primary data and secondary data are both used in research and statistics. They can be used to carry out
the same kind of research in these fields depending on data availability. This is because secondary data
and primary data have the same content. The only difference is the method by which they are collected.

Since the method of collection does not directly affect the uses of data, they can be used to perform
similar research. For example, whether collected directly or from an existing database, the demography
of a particular target market can be used to inform similar business decisions.

Conclusion

When performing research, it is important to consider the available data options so as to ensure that the
right type of data is used to arrive at a feasibility conclusion. A good understanding of the different data
types, similarities, and differences are however required to do this.

Primary data and secondary data both have applications in business and research. They may, however,
differ from each other in the way in which they are collected, used, and analyzed.

The most common setback with primary data is that it is very expensive, which is not the case for
secondary data. Secondary data, on the other hand, has authenticity issues.

DEMAND FORECASTING

Demand Forecasting Definition

Some of the popular definitions of demand forecasting are as follows:

Demand estimation (forecasting) may be defined as a process of finding values for demand in future
time periods.
Evan J. Douglas

Demand forecasting is an estimate of sales during a specified future period based on

 proposed marketing plan and a set of particular uncontrollable and competitive forces.
Cundiff and Still

Demand forecasting helps an organisation to take various business decisions, such as planning the
production process, purchasing raw materials, managing funds, and deciding the price of its products.

Demand can be forecasted by organisations either internally by making estimates called guess
estimate or externally through specialised consultants or market research agencies.

COMPONENTS OF DEMAND FORECASTING

Level of forecasting
Demand forecasting can be done at the firm level, industry level, or economy level. At the firm level,
the demand is forecasted for the products and services of an individual organisation in the future. At the
industry level, the collective demand for the products and services of all organisations in a particular
industry is forecasted. On the other hand, at the economy level, the aggregate demand for products and
services in the economy as a whole is anticipated.

Time period involved

On the basis of the duration, demand is forecasted in the short run and long term, which is explained as
follows:

 Short-term forecasting: It involves anticipating demand for a period not exceeding one year. It is
focused on the shortterm decisions (for example, arranging finance, formulating production policy,
making promotional strategies, etc.) of an organisation.

 Long-term forecasting: It involves predicting demand for a period of 5-7 years and may extend for
a period of 10 to 20 years. It is focused on the long-term decisions (for example, deciding the
production capacity, replacing machinery, etc.) of an organisation.
Nature of products
Products can be categorised into consumer goods or capital goods on the basis of their nature. Demand
forecasting differs for these two types of products, which is discussed as follows:

 Consumer goods: The goods that are meant for final consumption by end users are called consumer
goods. These goods have a direct demand. Generally, demand forecasting for these goods is done
while introducing a new product or replacing the existing product with an improved one.

 Capital goods: These goods are required to produce consumer goods; for example, raw material.
Thus, these goods have a derived demand. The demand forecasting of capital goods depends on the
demand for consumer goods. For example, prediction of higher demand for consumer goods would
result in the anticipation of higher demand for capital goods too.

IMPORTANCE OF DEMAND FORECASTING

Producing the desired output

Demand forecasting enables an organisation to produce the pre-determined output. It also helps the
organisation to arrange for the various factors of production (land, labour, capital, and enterprise)
beforehand so that the desired quantity can be produced without any hindrance.
Assessing the probable demand
Demand forecasting enables an organisation to assess the possible demand for its products and services
in a given period and plan production accordingly. In this way, demand forecasting avoids dependence
on merely making assumptions for demand.

Forecasting sales figures

Sales forecasting refers to the estimation of sales figures of an organisation for a given period. Demand
forecasting helps in predicting the sales figures by considering historical sales data and current trends
in the market.

Better control
In order to have better control on business activities, it is important to have a proper understanding of
cost budgets, profit analysis, which can be achieved through demand forecasting.

Controlling inventory
As discussed earlier, demand forecasting helps in estimating the future demand for an organisation’s
products or services. This, in turn, helps the organisation to accurately assess its requirement for raw
material, semi-finished goods, spare parts, etc.

Assessing manpower requirement

Demand forecasting helps inaccurate estimation of the manpower required to produce the desired
output, thereby avoiding the situations of under-employment or over-employment.

Ensuring stability
Demand forecasting helps an organisation to stabilise their operations by initiating the development of
suitable business policies to meet cyclical and seasonal fluctuations of an economy.

Planning import and export policies

At the macro level, demand forecasting serves as an effective tool for the government in determining
the import and export policies for the nation. It helps in assessing whether import is required to meet
the possible deficit in domestic supply.

FACTORS INFLUENCING DEMAND FORECASTING

Prevailing Economic Conditions

Demand forecasting can be affected by the changing price levels, national and per capita income,
consumption pattern of consumers, saving and investment practices, employment level, etc. of an
economy.

Thus, it is important that existing economic conditions should be assessed in order to align demand
forecasting with current economic trends.

Existing conditions of the Industry

The assessment of demand for an organisation’s products and services is also affected by the overall
conditions of the industry in which the organisation operates.
 For example, concentration of an industry increases the level of competition, which directly affects the
demand for products and services of different organisations in the industry. In such a case, demand
forecasted by organisations may falter.

Existing Condition of an Organization

Apart from industry conditions, the internal state of an organisation also affects demand forecasting.
Within the organisation, demand forecasting is affected by various factors, such as plant capacity,
product quality, product price, advertising and distribution policies, financial policies, etc.

Prevailing Market Conditions

in market conditions, such as change in the prices of goods; change in consumers’ expectations, tastes
and preferences; change in the prices of related goods; and change in the income level of consumers
also influence the demand for an organisation’s products and services.

Sociological factors, such as size and density of population, age group, size of family, family life cycle,
education level, family income, social awareness, etc. largely impact demand forecasts of an
organisation. For example, markets having a large population of youngsters would have a higher
demand for lifestyle products, electronic gadgets, etc.

Psychological Conditions
Psychological factors, such as changes in consumer attitude, habits, fashion, lifestyle, perception,
cultural and religious beliefs, etc. affect demand forecast of an organisation to a large extent.

Competitive Conditions
A market consists of several organisations offering similar products. This gives rise to competition in
the market, which affects demand forecasted by organisations.

For example, reduction in trade barriers increases the number of new entrants in a market, which
affects the demand for products and services of existing organisations.

Import – Export policies

The demand for export-import goods gets directly affected by changes in factors, such as import and
export control, terms and conditions of import and export, import/export policies, import/export
conditions, etc.

Steps in Demand Forecasting

Specifying the objective
The purpose of demand forecasting needs to be specified before starting the process. The objective can
be specified on the following basis:

 Short-term or long-term demand for a product

 Industry demand or demand specific to an organisation
 Whole market demand or demand specific to a market segment
Determining the time perspective
 Depending on the objective, the demand can be forecasted for a short period (2-3 years) or long period
(beyond 10 years). If an organisation performs long-term demand forecasting, it needs to take into
consideration constant changes in the market as well the economy.

Selecting the method for forecasting

There are various methods of demand forecasting. However, not all methods are suitable for all types
of demand forecasting. Depending on the objective, time period, and availability of data, the
organisation needs to select the most suitable forecasting method. The selection of demand forecasting
method also depends on the experience and expertise of the demand forecaster.

Collecting and analysing data

After selecting the demand forecasting method, the data needs to be collected. Data can be gathered
either from primary sources or secondary sources or both. As data is collected in the raw form, it needs
to be analysed in order to derive meaningful information out of it.

Interpreting outcomes
After the data is analysed, it is used to estimate demand for the predetermined years. Generally, the
results obtained are in the form of equations, which need to be presented in a comprehensible format.

LIMITATIONS OF DEMAND FORECASTING

Lack of historical sales data

Past sales figures may not always be available with an organisation. For example, in case of a new
commodity, there is unavailability of historical sales data. In such cases, new data is required to be
collected for demand forecasting, which can be cumbersome and challenging for an organisation.

Unrealistic assumptions
Demand forecasting is based on various assumptions, which may not always be consistent with the
present market conditions. In such a case, relying on these assumptions may produce incorrect forecasts
for the future.

Cost incurred
Demand forecasting incurs different costs for an organisation, such as implementation cost, labour cost,
and administrative cost. These costs may be very high depending on the complexity of the forecasting
method selected and the resources utilised. Owing to limited means, it becomes difficult for new
startups and small-scale organisations to perform demand forecasting.

Change in fashion
Consumers’ tastes and preferences continue to change with a change in fashion. This limits the use of
demand forecasting as it is generally based on historical trend analysis.

Lack of expertise
Demand forecasting requires effective skills, knowledge and experience of personnel making forecasts.
In the absence of trained experts, demand forecasting becomes a challenge for an organisation. This is
because if the responsibility of demand forecasting is assigned to untrained personnel, it could bring
huge losses to the organisation.
Psychological factors
Consumers usually prefer a particular type of product over others. However, factors, such as fear of
war and changes in economic policy, could affect consumers’ psychology. In such cases, the outcomes
of forecasting may no longer remain relevant for the time period.

METHODS OF DEMAND FORECASTING

There is no easy or simple formula to forecast the demand. Proper judgment along with
the scientific formula is needed to correctly predict the future demand for a product or
service. Some methods of demand forecasting are discussed below:

1] Survey of Buyer’s Choice

When the demand needs to be forecasted in the short run, say a year, then the most
feasible method is to ask the customers directly that what are they intending to buy in
the forthcoming time period. Thus, under this method, potential customers are directly
interviewed. This survey can be done in any of the following ways:

a. Complete Enumeration Method: Under this method, nearly all the potential buyers are
asked about their future purchase plans.
b. Sample Survey Method: Under this method, a sample of potential buyers are chosen
scientifically and only those chosen are interviewed.
c. End-use Method: It is especially used for forecasting the demand of the inputs. Under
this method, the final users i.e. the consuming industries and other sectors are identified.
The desirable norms of consumption of the product are fixed, the targeted output levels
are estimated and these norms are applied to forecast the future demand of the inputs.
Hence, it can be said that under this method the burden of demand forecasting is on the
buyer. However, the judgments of the buyers are not completely reliable and so the
seller should take decisions in the light of his judgment also.

The customer may misjudge their demands and may also change their decisions in the
future which in turn may mislead the survey. This method is suitable when goods are
supplied in bulk to industries but not in the case of household customers.

2] Collective Opinion Method

Under this method, the salesperson of a firm predicts the estimated future sales in their
region. The individual estimates are aggregated to calculate the total estimated future
sales. These estimates are reviewed in the light of factors like future changes in the
selling price, product designs, changes in competition, advertisement campaigns, the
purchasing power of the consumers, employment opportunities, population, etc.
 The principle underlying this method is that as the salesmen are closest to the
consumers they are more likely to understand the changes in their needs and demands.
They can also easily find out the reasons behind the change in their tastes.

Therefore, a firm having good sales personnel can utilize their experience to predict the
demands. Hence, this method is also known as Salesforce opinion or Grassroots
approach method. However, this method depends on the personal opinions of the sales
personnel and is not purely scientific.

3] Barometric Method
This method is based on the past demands of the product and tries to project the past
into the future. The economic indicators are used to predict the future trends of
the business. Based on future trends, the demand for the product is forecasted. An
index of economic indicators is formed. There are three types of economic indicators,
viz. leading indicators, lagging indicators, and coincidental indicators.

The leading indicators are those that move up or down ahead of some other series. The
lagging indicators are those that follow a change after some time lag. The coincidental
indicators are those that move up and down simultaneously with the level of economic
activities.

4] Market Experiment Method

Another one of the methods of demand forecasting is the market experiment method.
Under this method, the demand is forecasted by conducting market studies and
experiments on consumer behavior under actual but controlled, market conditions.

Certain determinants of demand that can be varied are changed and the experiments are
done keeping other factors constant. However, this method is very expensive and time-
consuming.

5] Expert Opinion Method

Usually, market experts have explicit knowledge about the factors affecting demand.
Their opinion can help in demand forecasting. The Delphi technique, developed by
Olaf Helmer is one such method.

Under this method, experts are given a series of carefully designed questionnaires and
are asked to forecast the demand. They are also required to give the suitable reasons.
The opinions are shared with the experts to arrive at a conclusion. This is a fast and
cheap technique.
6] Statistical Methods
The statistical method is one of the important methods of demand forecasting.
Statistical methods are scientific, reliable and free from biases. The major statistical
methods used for demand forecasting are:

a. Trend Projection Method: This method is useful where the organization has a
sufficient amount of accumulated past data of the sales. This date is arranged
chronologically to obtain a time series. Thus, the time series depicts the past trend and
on the basis of it, the future market trend can be predicted. It is assumed that the past
trend will continue in the future. Thus, on the basis of the predicted future trend, the
demand for a product or service is forecasted.
b. Regression Analysis: This method establishes a relationship between the dependent
variable and the independent variables. In our case, the quantity demanded is the
dependent variable and income, the price of goods, the price of related goods, the price
of substitute goods, etc. are independent variables. The regression equation is derived
assuming the relationship to be linear. Regression Equation: Y = a + bX. Where Y is the
forecasted demand for a product or service.

Marketing Planning – Meaning

Planning is deciding in advance what to do, how to do it,
when to do it and who is to do it. Planning is simply a
rational approach to accomplish an objective. It bridges
the gap from where we are & where we want to go.
Planning is the first management function to be
performed in the process of management. It governs
survival, growth and prosperity of any enterprise in a
competitive and ever changing environment.
Planning is an analytical process which covers:
1. Analysis of the situation or environment,
2. Assessment of the future opportunities and threats,
3. Determination of objectives and goals in the light of
the future environmental forces and
4. Selection of the best strategy or the course of action from
among the alternative strategies to achieve the objectives.
Planning is the first and the foremost function of management.
Planning precedes all the functions. Marketing planning is the
starting point of all marketing and business activities of an
enterprise. Because of the dynamism of the environment, the role
of marketing planning has increased a lot.

Many experts today consider marketing planning as synonymous

with overall business planning because the purpose of any
business is the successful management of its markets (marketing
resources).

Marketing planning is the process – Marketing planning is a

process that consists of analyzing current situation and
information about marketing opportunities, forecasting and
establishing planning premises, selecting target market(s),
determining marketing objectives, designing and developing
marketing strategy or courses of action for achieving these
objectives and allocating resources to the ingredients of
marketing effort i.e. marketing mix and developing procedure
and policies.

Every company must look ahead and determine when it wants to

go and how to get there. Its future should not be left to chance. To
meet this need, companies use two systems — a strategic
planning system and marketing planning system. Strategic
planning provides the route map for the firm. Strategic planning
serves as the hedge against risk and uncertainty.
Strategic planning is a stream of decisions and actions which lead
to effective strategies and which in term help the firm to achieve
its objectives. Strategy is not something that can be taken out of
one’s packet and pushed into the market all of a sudden. No
magic formula exists to prepare for the future.

The requirements are excellent insight to understand changing

consumer needs, clear planning to focus our efforts on meeting
those needs, and flexibility, because change is the only constant.
Most important, we must always offer products of quality and
value to the consumers.
 Marketing planning is the process of anticipating future events
and developing strategies to achieve organisational objectives. It
involves designing activities relating to marketing objectives.
Marketing planning of an organisation is planning for that
organisation’s revenue-generating activities.
Marketing Planning – Why is Marketing Planning
Essential?
‘It is planning, not gambling, that produces profits and security.’
Organizations operate in increasingly fragmented, complex and fast-changing
markets. Meeting the challenges presented by a highly fluid and competitive
environment normally means experiencing conflicting pressures between business
objectives.
(i) Enhancing customer service versus increasing profitability.
(ii) Short-term profit versus long-term value creation.
(iii) Maximization of revenue versus minimization of costs.
Marketing planning is an effective aid to management because of
its integral role in identifying and clarifying the priorities for the
business. Without a clear statement of priorities, the company is
vulnerable to internal confusion and lost opportunities.
The following list describes the most common
symptoms of a reliance on traditional sales forecasting
and budgeting procedure in the absence of a marketing
planning system:
(i) Lost opportunities for profit
(ii) Meaningless numbers in plans
(iii) Unrealistic objectives
(iv) Lack of actionable market information
(v) Inter-functional strife
(vi) Management frustration
(vii) Proliferation of products and markets
(viii) Wasted promotional expenditure
(ix) Pricing confusion
(x) Growing vulnerability to environmental change
(xi) Loss of control over the business
An effective marketing planning system should offer more than immunity against
these operational problems- it should deliver clearer and more widely understood
objectives and priorities, higher levels of usable market information, improved
 inter-functional coordination, less waste and duplication of resources, and greater
overall business control.
A Business Week survey in 1996 indicated that as few as 6 per cent of business
people in the USA would rate their company as excellent at planning for the long-
term future. Could this be because they have not mastered the art of planning, or
because they suffer from a short-sighted business outlook, or because their
organizations contain barriers to marketing planning?

Marketing Planning – Scope: Long Term and Short Term

Marketing Planning
The activities of marketing planning are generally divided into two divisions
according to time—(a) Long term Marketing Planning; and (b) Short term or
annual Marketing Planning.