DEMAND PLANNING IN RETAIL
Accurate demand planning is essential, as it ensures that you
always have the right products on your shelves.
Correctly predicting customer demand also means that stores
don’t have lots of unsold inventory that ties up valuable capital.
In this post, you’ll learn how demand planning contributes to
better supply chain management.
What is demand planning?
The term demand planning is part of the supply chain
management cycle. As a retailer, you are forecasting a product’s demand so
there are always enough items on the shelves for customers to buy.
You also want to avoid a surplus of products. Excessively high
inventory levels reduce your capital and impact your profitability.
Factors that influence
product demand
Several factors can influence a specific product’s customer
demand, including:
·
The economic
performance of your country, region, market, etc.
·
Weather conditions
·
Seasonal fluctuations
·
Political disruptions
· Pop culture and trends
It’s important to obtain demand-related information from all
possible sources. Analysing consumer trends and past sales data can often prove
useful. Together, these factors enable you to improve your forecast accuracy
and match those numbers with your supply forecast.
Why is demand planning
important?
Skilled demand planners know the importance of making accurate
forecasts. First, you’ll avoid undesirable stock-outs that increase the chances
of customers switching to a competitor. Obtaining accurate demand information
also simplifies inventory management and operations planning functions.
When to conduct demand
planning
Ideally, you’ll perform demand planning tasks on an almost
real-time basis rather than relying on historical data. As a starting point,
pay attention to the demand signals you receive during your daily operations.
This nuts-and-bolts information comes from actual retail sales and product
order information.
Demand sensing activities are also useful for enhancing
near-future forecasts for the next few hours or days. This method uses demand
data sourced from short-term activities.
Enhance these two types of data with targeted demand planning
applications. More timely data acquisition enables better decision-making and
more accurate product performance metrics. In turn, this leads to more
efficient supply chain management.
If you don’t regularly perform these demand management tasks,
you may encounter significant product shortages. You could also be burdened
with excess and/or obsolete inventory that customers won’t buy at any price.
Demand planning vs. demand
forecasting
Demand planning refers to the entire process of predicting a
product’s sales. Within this larger context, demand forecasting covers a
longer-term period such as the next 18 to 24 months. However, the forecast
timeframe often varies by industry and type of product.
Reviewing sales data, and monitoring changing market conditions,
will help you to better forecast demand for a specific product. Using the
service levels concept provides an indication of the chances of having
sufficient stock to satisfy customer demand. Based on this information, you can
refine the forecasting process accordingly.
7 steps for effective demand
planning
When you implement a workable demand planning process, you’ll
find that sales and operations planning (or S&op) are also much easier. In
turn, this sets the stage for more productive business planning.
Let’s say you can successfully predict demand for a certain
product (or SKU, short for “stock keeping unit”). Then, you’ll have an
indication of which product lines will be profitable for your business. This
knowledge can drive your product portfolio and subsequent new product
introductions.
Demand planning in action
The demand planning management process involves internal
stakeholders and external partners such as product vendors. Participants will
review varied forecasting methods and choose the one deemed most appropriate
for the business’ needs.
1. Assemble a
cross-functional team
Gather team members from every department involved in the
product lifecycle. Supply chain planning and purchasing team members should be
dedicated to ensuring sufficient inventory to fulfill the demand forecast.
Finance department team members will create the demand forecast. Each
participant should have well-defined roles and related responsibilities.
2. Obtain agreement on
relevant details
All team members should decide on the data needed for a
high-value forecast. Common data metrics include sales data, inventory
turnover, out-of-stock frequency, and production lead times.
To enable informed decision making, product teams will provide new product and
product retirement details. Sales and marketing team members will present
information on price adjustments, promotions, and marketing campaigns that
could impact demand.
3. Add relevant external data
Varied external factors will likely affect the demand forecast.
Examples include supplier/distributor delivery performance and key customer
buying habits. Large-scale economic trends, significant market shifts, and
changes in demand for specific products are other factors.
4. Produce your demand
forecast
Team members should select the most relevant statistical
forecasting model for the retailer’s needs. Although some retailers still use
relatively laborious Excel spreadsheets, most companies have opted for powerful
demand planning software.
Depending on the forecasting model, artificial intelligence, machine learning,
and/or algorithms may also be involved. These forecasting methods easily
automate the processing of huge datasets.
These sophisticated forecasting models can also identify
obscure patterns and trends. Demand planners can utilize this data to make near
real-time adjustments.
Larger retailers may use enterprise resource planning (or ERP)
software that integrates varied aspects of the business’ operations. If
necessary, conduct a webinar to familiarize all team members with the chosen
forecasting method.
5. Review the draft demand
forecast
Convene the team members, and verify all relevant forecast
information. Consider removing unusual data that could unnaturally skew the
forecast.
Add recently available data to determine whether it significantly affects the
predictions. Finally, ensure that the demand forecast syncs with the company’s
larger-scale financial forecasts.
6. Compare forecasts vs
inventory
Identify the amount of inventory necessary to meet the projected
demand (including some extra “buffer inventory”). Ensure that specified vendors
can meet the demand on time. Confirm that transportation contractors can meet
your schedule and volume demands.
7. Implement specific
measurement criteria
Define key performance indicators (or KPIs) that enable
effective demand planning evaluation and optimization. Assign target levels for
factors such as sales forecasting accuracy and order fulfilment lead time,
among others.
Methodically review actual performance vs the targets, and
implement adjustments as needed. This “bottom-up” approach evaluates a specific
process or function. Then, the retailer can incorporate those results into
larger-scale company operations.
Looking ahead: the future of
demand planning
Technology advances have led to the development of powerful
demand planning software that improves forecast accuracy. Machine learning,
artificial intelligence, and/or algorithms may be integrated into the software
program.
Companies may utilize Internet of Things (or IoT)-enabled
devices to receive real-time data on inventory or raw materials. IoT technology
also enables real-time sales monitoring that drives faster replenishing of
store inventories.
Communications and collaborative skills are also important in
this digital business landscape. Working effectively with internal and external
stakeholders helps to ensure that everyone’s goals will be met.
Combined digital technologies will continue to improve a retailer’s
ability to predict customer demand for their products. To satisfy this demand,
the retailer orders more products through their established supply chain.
Ideally, suppliers deliver the merchandise in time to avoid
potentially costly stock-outs. Over time, this successful demand strategy will
help the business to grow.