The demand planning process also helps manufacturers
better understand profit potential.
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Working with clients, not just for them
W H I T E
P A P E R
Demand Planning
Across the Enterprise
Demand planning is kind of like weather forecasting
– little credit is given when the forecast is correct, but
much notice is taken when it’s wrong. That’s probably
because getting it wrong can be costly. Much time and
effort is spent on continuous improvement and working
on how to better use forecasts for decision making.
Despite these efforts, excellence in demand
management still eludes many manufacturing
companies. Demand planning is often viewed with
disillusionment, resulting in organizational skepticism
about the chances of making meaningful improvements
to the process.
Recent manufacturing industry surveys identify
shrinking profit margins requiring cost efficiencies, the
need to improve customer service levels and market
volatility resulting in high demand uncertainty as the top
three pressures driving interest in demand forecasting
and planning. On average, companies with more
accurate demand forecasting and planning capabilities
have less inventory, better perfect-order ratings and
shorter cash-to-cash cycle times than others. Surveys
have also shown that demand forecast accuracy leads
directly to higher return on assets and improved profit
margins. Further benchmarking reports show that for
every 1% improvement in forecast accuracy, companies
report a 1-2% drop in inventory levels.
Challenges in Demand Planning
Unfortunately, the reality is that “forecastability” of
demand is more difficult today than it ever has been in
the past. Demand unpredictability is growing with an
abundance of new products and constantly changing
needs of customers. In addition, demand data is
becoming more complex and traditional approaches to
forecasting and demand planning are not particularly
effective in predicting market demand and managing
the volatility in today’s markets.
The Business Case for Demand Planning
What’s a company to do? If the actual almost never
equals the plan, why should we sweat the details?
There are several compelling reasons not to give up
on demand planning. An accurate demand forecast is
important for production and distribution management
but also for areas of marketing and sales (distribution
of sales forces, communication, promotion and
planning of new products), finance (cash flow and
budgets), investment decisions (production facilities
and warehouses), and human resources (staffing levels).
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There are many challenges to accurate forecasting of
demand planning:
•
Getting timely customer demand data is difficult.
•
New product forecasting is problematic because of a
lack of historical demand patterns.
•
Volatility in market demand and introduction of
new disruptive products makes traditional forecast
modeling ineffective because past trends are no
longer accurate indicators of the future.
•
Understanding the effects of sales promotions,
marketing events and economic factors is
sometimes omitted from modeling, resulting in
misalignment of forecasted and actual demand.
•
Functional silos prevent efficient demand planning.
This practice leads to poor coordination among
organizational units, produces inconsistent results,
and leads to wasted opportunities in optimizing
operational costs and efficiencies.
They Get The Process Right
It’s important for manufacturers to decide upfront what
data they need to plan demand. This is different for every
company based on their business model, product mix,
and market dynamics. Some companies analyze and plan
demand at the product level, customer level or geographic
level. No matter what the inputs are to your process, you
should review them regularly and be prepared to change
how you plan demand based on changes in your business,
the economy, or the markets you operate in.
Next, make sure the decisions you make translate into
your master data models. All business units, regions,
departments and facilities should be using common
master data to do their demand planning. Make sure that
everyone companywide is using common definitions
and understanding of things such as:
•
Master data and its attributes
•
Groups and hierarchies for aggregating and
disaggregating demand data
Characteristics of Successful
Demand Planning Processes
•
Organizational hierarchies for locations and
organizational units
Companies who report high satisfaction with their
demand planning processes tend to have some common
characteristics. Below are some key requirements for a
successful demand planning process:
•
Time & horizon definitions
•
Consistent definitions for units of measure
•
Pricing, discounting, promotional terms, etc.
Demand Planning entails the use of analytics to use market signals
such as sales, customer orders, customer shipments, or market
indicators to predict future demand patterns.
Demand Planning Across the Enterprise Page 2
It is also important to establish the frequency of
forecasting and methods of analysis. When you have
different groups using different data, different planning
horizons or different historical data, it will be extremely
difficult to use the resulting forecasts for decision
making across the enterprise. It is important to create
an integrated enterprise level business planning process
that drives the business forward.
Key Requirements for a
Successful Demand Planning
and Forecasting Process
¨¨ A single demand forecast with cross-functional
input across the enterprise
¨¨ Integration with the order management, sales,
marketing and operational processes
They Have a Single Version of the Truth
Given the potential use of demand forecasts in driving
many other processes, it is critical for companies to have
a single forecast to ensure alignment among all the
downstream processes. Unfortunately, this is not always
the case. It is actually quite common that companies
use many different demand forecasts in their decision
making. This leads to inconsistent demand projections
being used for different processes, which ultimately leads
to plans that are misaligned with operations. Lack of
alignment between planning and operations can result
in ill-advised capital investments, bloated inventories
and missed targets for revenue, profitability & budgets.
¨¨ Performance metrics to measure ROI
¨¨ Real-time reporting of metrics across the
enterprise
¨¨ What-if analysis and scenario planning
¨¨ Modeling capabilities that can take into account
both internal (i.e; promotions, marketing
events, competitor actions) and external (I.e.:
natural disasters, economic activities, regulatory
changes) events
¨¨ Ability to segment demand using both product
and customer characteristics
They Embrace Collaboration and Integration
A key requirement for efficient company management
is sharing the mutual forecast. Demand planning is
a collaborative process. While the data and statistics
are crucial, the real value comes from the knowledge
your team brings to the process. Manufacturers must
embrace a more transparent and collaborative process to
ensure that functional plans that share critical inputs like
projected demand are vetted and shared widely across
the enterprise to support critical decision making. This can
be achieved by establishing a clear process and having
a tool capable of manipulating the demand forecasts to
meet the needs of the separate business functions.
create forecasts, demand planning systems should have
the ability to manipulate the data and create multiple
views for the different functions within the company.
A good demand planning solution must also allow
modeling and working with the basic dimensions of
demand – product, location, and time. This also provides
a flexible framework to manipulate data along these
dimensions & create views that are most relevant for
the process under consideration. For example, product
attributes like sales velocity, formula/recipe/product
family or targeted customer segment provide for
grouping and reviewing demand at aggregated levels
relevant to different processes. Having the ability to
model such attributes and manipulate data using these
attributes is an integral part of an effective solution. Here
are a couple of examples:
Picking the Right Tool
Manufacturers need tools that provide the flexibility to
use a single source of demand history and create many
different forecast series as required by the planning
process and the related processes it supports. In addition
to basic functional capabilities such as the ability to
Demand Planning Across the Enterprise Product Views: Creating a hierarchy along the product
dimension allows users to create product categories and
Page 3
to aggregate data to look at demand by category, product
group, department, and so on. The solution must allow for
both a roll up of products into a product family that groups
them together for use in marketing and sales processes,
but can also present data in an inventory group hierarchy
to quickly manage inventory levels. For example, the
inventory groups may be created by using an attribute
that models the sales velocity of the individual products,
while the marketing categories may need to see attributes
like brand and target customer segment. Having multiple
hierarchies allows the users to aggregate demand data for
their specific process needs.
Horizon Modeling: This helps the users to construct both
finely defined time periods for short term forecasting
and more aggregate timelines for future time periods.
This makes the solution more responsive and allows for
modeling longer time horizons as well. It also reduces
forecasting errors by aggregating demand for the farthest
time periods. For example, the immediate time periods
can be defined as days, followed by weeks, followed by
months and quarters.
Companies Grow.
Revenues Grow.
Opportunities Grow.
For a more comprehensive list of key requirements, see
the side bar Key Requirement for a Successful Demand
Planning and Forecasting Process
Summary
The world of demand planning has changed. Business
requirements have escalated and it matters more than
ever. Few process manufacturers can afford the financial
risks and costs associated with bad forecasts and bloated
inventories. Manufacturers stuck in the past with oldline forecasting methods face limits not only on their
profitability and improvement potentials, but also on their
opportunities to become more flexible in response to
shifting customer demand.
Effective demand planning doesn’t just happen, it requires
work. It is imperative that manufacturers implement
demand planning solutions that will allow them to create
a single demand forecast to drive their critical processes
across the enterprise. Cross-functional alignment in plans
and operations will establish process collaboration, reduce
plan conflicts and volatility, and create operational stability.
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Demand Planning Across the Enterprise Page 4