Demand
forecast is the cross functional document that is
aligned for the incoming period. The Sales
forecasting methods should involve all
stakeholders, not just sales department. Although
the sales can set volume targets, they can be
unrealistic in some cases. They can be higher or
lower than real demand, due to tactical reasons,
but they can also be reflection of wishful
thinking than the real demand forecast.
Unrealistic demand
forecast can create serious consequences along
the organization. If the demand is estimated
too high than is real demand, there is a risk of
product obsolesce. Once the product approaches the
expiry date, the chances for customers to accept it
are minimal. Write off is causing direct negative
impact on profit of the company. As the chain
reaction, the raw material can also become obsolete
in case that sales volume is much lower than
initially planned. Secondary negative effect of
overestimated volume is increase of stock in
warehouse. This is causing related costs, e.g.
additional warehouse renting due to overstocking.
On
the other hand, if the demand forecast is lower than
the real demand, the risk of stock out ( out of
stock ) is possible. The stock out is leading to
direct loss of profit, due to lost sales
opportunity. As a secondary effect, the service
level is compromised, which leads to retailer's
dissatisfaction and potential deterioration of
future co-operation. Finally, the consumer is
tending to switch to another brand in case that
stock-out is frequent.
Therefore,
the choosing the right forecasting methods is
crucial decision for proper inventory management. The
correct forecasting method for demand forecasting requires
involvement of all stakeholders, primarily sales and
supply chain. The good approach to sales forecast
starts with:
Sales
analyst / demand planner is calculating the
historical forecast based on the same period of
previous years and trends of several previous
months of current. The historical forecast is estimated on
the level of every SKU. This approach is
continuing along the process.
Since
the sales of previous years can have some
deviation caused by different factors, it is
necessary to normalize the historical forecast.
The normalization requires a good database of
previous years promotions, stock-outs, or any
other factor that influence sales volume.
Normalization means flattening the sales curve
for the factors that occurred in the last year
and are not likely to happen in this year. Promotion that
happened last year caused volume increase. In
case that promo is not taking place this year
than it is necessary to deduct this incremental
volume. On the other case, if there was
stock-out at the same period of previous year,
while the stock-out is not anticipated for this
year, than it is necessary to fill the gap on
the curve of historical demand.
Now
when the sales forecast is normalized, it is
necessary to enrich it with the current
promotions. Expected volume incremental should
be added on top of normalized sales forecast.
Enriched
sales forecast should now
be revised by sales
people, usually high
position managers. They need to give their
input, based on the current trends in the
market, information from the customers,
competition activities, and most of all from
their experienced.
Next
step is alignment of demand forecast with
supply chain. Up to now the sales forecast is
just the imaginary plan. The supply chain is
supposed to materialize this plan, meaning to
purchase raw materials, produce the product,
store it and finally to deliver it to the
customers, as per sales orders. The supply
chain is giving feedback on the sales
forecast, regarding feasibility and potential
restrictions.
Once
the supply chain is returning feedback to
demand planner, the final adjustments are
done. This is considered to be the final
unconstrained demand forecast.
The
process of demand forecast alignment is very
complex and time demanding forecasting method. Still it is very
important, since errors in forecast are creating
inevitable losses to the company. In order to
track efficiency of sales forecast, it is
necessary to track sales forecast accuracy.
