Demand Planning: The first step in Supply Chain planning

Demand planning or sales forecasting is one of the
most important aspects of any organization, be it in
the services or the manufacturing sector. A services
organization estimates demand for its services and
thereby gears itself up to service demand. A
manufacturing organization estimates demand for its
manufactured goods and works towards activities such as the
supply of raw materials, production capacity, distribution etc.
Demand planning plays a strategic role in any organization as the
planning for a lot of other activities depends on the accuracy and
validity of this exercise. For example, sales and operations
planning is an important function and in some organizations this
planning cycle is triggered once the demand forecasting cycle is
closed. There are many pieces of software available in the market
which help us conduct demand planning in an effective manner.
One of the most widely used of these is Microsoft Excel. Most of
the ERP products like SAP, Oracle Applications and SCM products
like i2 have Demand Planning functionality available in their suite
of product offerings. This article explores some important
functionalities and features that are useful for organizations in
demand planning.

􀁺 Statistical forecasting: Most demand planning exercises
start with a statistical forecast. There are various models,
each catering to different behavioral patterns shown by
products and markets. These include univariate models,
linear models, the multivariate linear and non linear models,
seasonal models, Croston’s model, mixed model etc. The list
is virtually endless. They may look like small words but
selecting an appropriate model for each of the products in a
portfolio can be a time consuming and intricate task. There
are no shortcuts here. A detailed simulation exercise needs
to be carried out to select the best model for a product and
market. Statistical forecasting models need to be
continuously tested and refined. This means that the
demand planning tool should also support a simulation
environment and also the ability to compare different
forecasting models. Depending on the way that data is
stored in the demand planning tool, statistical forecasting
can be done at various levels. There can be a top down
approach or a bottom up approach. A top down approach
means carrying on statistical forecasting at the highest level
and then breaking it down, while the bottom up approach is
the exact opposite.
􀁺 Consensus planning: The demand planning tool should
support consensus planning features since demand planning
is rarely the work of a single person or a single department.
Demand planning is often a collaborative exercise between
different departments and people, who bring in their years of
expertise. That is why a tool should be able to capture their
inputs on top of statistically forecasted numbers.
􀁺 Promotional planning features: The demand planning
tool should also be able to handle promotional planning. An
extensive promotional planning feature is a great asset for
any organization. It helps plan promotions and the effect of
said promotions on other products, like cannibalization.
Cannibalization can be extremely difficult to capture as it not
only affects one’s own product lines in a similar category but
also products in other categories.
􀁺 Lifecycle management: Planning for the demand of a
product spanning its lifecycle is a complex process. They
may not be a simple introduction of new products or phasing
out of existing products; the situation could also call for
replacing an existing product with a new product or multiple
products. Product substitution functionality should be an
integral part of a demand planning tool. This might seem
extremely simple but technically it requires a lot of features,
like the ability to copy historical sales of one product into
another, the ability to play around with he sales figures of
one geographical area in another area etc.
􀁺 Seasonal planning: Seasonal planning is an intriguing
process. It can be a difficult thing to simulate in statistics
with a reasonable degree of accuracy if demand patterns are
not regular. The complexity is due to the fact that festival
seasons can fall in different months of the year in different
years. The time span or the duration of a particular season
could be different in different years. For example winter can
be lengthy one year and shorter next year.
􀁺 User interface: Most organizations start demand planning
with Microsoft Excel. Any organization would vouch for the
fact that Excel is easy to use and over the years they have
become quite comfortable with it. Thus, it makes great sense
if the user interface of the demand planning tool is
comfortable and user friendly. This makes it easy to get
acceptance from the end users.
􀁺 Data management and archival: Another important
feature of any demand planning tool is the ability to churn a
huge amount of data in a reasonable period of time. It
should also be able to archive old data for reference. This
archival process should be easy and should not affect the
current functionality of the product. If a demand planning
tool is built on the data warehousing backbone it can have
great ability to play around with data in many dimensions.
This also makes it feasible to have statistical data forecasting
at various levels not only at the lowest level at which data is
captured. A data warehousing backbone also makes it easy
to look at the data’s various dimensions and levels increasing
the utility of demand forecasting and planning manifold.
There are various other interesting features which would be
important for an organization. Demand forecasting and planning is
the first step in most planning cycles in any organization. Any
errors that creep into the numbers at this point have a ripple effect
later on which only gets amplified. This phenomenon is popularly
known as the Bullwhip effect in supply chain. With the ever
changing nature of the environment that an organization is
operating in along with shortening product lifecycles and other
competitive pressures it is imperative to have a demand planning
tool which should be able to handle the complexities of the
business not only today but also for the future needs of an
organization as it grows.
Originally published by Express Computers.