Do you know
what is the difference between a salesman and a sales and marketing
consultant? A salesman just shows up to get you to buy something
that you might not even want or need. A sales and marketing consultant
drops by to see if there is anything he can do to help you get what
you need. This is a big difference, and it is the main reason why
more sales strategies involve the concept of consultative sales
instead of direct selling. Our Consultant Marketing Sales Training
classes will help you not only grasp the differences between these
two selling styles, but we will help you develop the sales skills
you need to become an effective sales consultant.
Forecasting demand is never
easy; here are some tips for making the process work for you.
It's 7:00 p.m., and your
favorite restaurant has already run out of the day's special entrée.
You wonder, didn't they expect it to sell? Another time, you save money at the
"end of season blow-out sale." The cool summer slowed swimming suit
sales, and while the store is clearly losing out, you are the lucky bargain
hunter, paying less than half the original price.
Restaurants and clothiers
are not the only ones to suffer from the challenges of predicting
demand for goods and services. Whether selling back-to-school items
or greeting cards, service
calls or insurance, businesses need to be able to confidently
forecast demand. It's essential: Having a good idea of what's coming
may improve customer service, but it can also make a big difference
in sales and profits.
Where do you begin? There are nearly
as many ways to forecast as there are business owners. Some companies forecast
informally - a gut feel, or a few numbers scratched on the back of a cocktail
napkin. Some pay statisticians to work with expensive software to develop predictions
of the future. Regardless of method, few forecasts are ever right.
The issue is not getting an accurate forecast; the issue is getting
one good enough for the decisions at hand. It must be worth more
in the information it provides than it costs to develop. So how
do you do that? Software alone is not the answer, and may not be
the answer at all. As you work to improve
your ability to see the future, consider these four key steps
to shaping a forecasting strategy that will work for your business:
First, understand your business.
Your understanding of your business
is more important to good forecasting than almost any other factor. Don't leave
forecasting to the software or the equations. Make sure you can say, "This
seems reasonable" for both the forecast model used and the forecast itself.
For example, your industry may have
an annual show in November that always pumps up demand. Since your historical
data reflects that bump, a statistical forecast of future demand would also
plan that bump. But what if that show is being moved to October next year? A
good forecast would plan for the show-induced increase in sales to happen earlier.
Your understanding of your business is what would tell the forecast model to
incorporate that change.
Develop a relevant forecasting
Forecasting cannot be an
event; it must be a process. To get forecasts that will help you
make informed decisions, you must define steps to ensure you are
using the right data, that the forecast models used make sense,
and that the forecast is used in the way it was intended. You need
to define responsibilities and timing
requirements. It is less important where the responsibilities
lie, and more important that they are defined, accepted, and executed
within the timing rules of your process. Ignoring these issues makes
a good forecast is a matter of luck, not planning.
As an example
of "right data," consider this: Some of you use shipment
or billing history as a basis to forecast the future. Ask yourself,
does that data really reflect what and when the customer wanted?
If you have a history of late deliveries or product substitutions,
then customer order data could better reflect what the customer
wanted. If you are going to use the past to predict the future,
make sure the history data you use reflects the assumptions you
want to make about the future.
Understand how the forecast will
"Please have a forecast
on my desk at 8:00 a.m. tomorrow morning." That assignment
cannot be effectively accomplished until you know what kind of decisions
will be made using the forecast. For example, the decision to work
overtime this weekend requires a much more near term and more detailed
forecast than the decision to buy land to build a new facility two
years from now. The end goal of forecasting
is NOT to generate a forecast; it is to support improved decision-making.
Every time you create a forecast,
you must choose a level of detail and length of the planning horizon. A forecast
can be for dollars, product family units, or part number detail; it can be for
annual, quarterly, monthly, daily, hourly time buckets; it can look out a day,
a quarter, a year. Once you understand the decision that will be made using
the forecast, you can construct the forecast appropriately.
Choose an appropriate model.
There are lots of forecasting models
you can use. Some are as simple as projecting this month's sales based on last
month's sales, while others deploy very sophisticated mathematics. There is
no reason to assume that fancier models are better. I have seen a simple 3-month
or 6-month moving-average forecast beat out more complicated models many times.
If you have forecasting
software, review the numbers it provides in assessing the accuracy
of different models. If you don't have forecasting software, a simple
spreadsheet can be invaluable. To check how well your model works,
use it to predict the last 3 months and compare it to what you know
did happen. Is the forecast model you used close enough for your
purposes? If so, use it. If not, try another model and see how well
it would have done. Keep doing that until you find a model that
seems to work for you. Your knowledge
of your business will be critical in choosing models that make
sense to try.
Key point: Avoid models that require
more mathematical or statistical expertise than your forecasters and users of
the forecast have. If your business requires complex models, and some do, then
make sure the appropriate personnel are trained in their use and interpretation.
Don't trust the software alone.
Sales Training - Forecasting
Is Never Easy
Marketing Sales Quote
There is a real magic in enthusiasm.It spells the difference between mediocrity
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