Supply Chain World - Fall 2017 - 15

FORECASTING

Data-mature organizations have
invested in advanced analytical
applications that bring together
sales and operations.

BY NEAL GOFFMAN

Are You A
Leader?
Executive teams need accurate
forecasts to set performance
benchmarks and optimize targets for revenue, profit, territory,
pipeline opportunity and more.
Production and procurement
teams need them to optimize
required resources such as raw
materials, people and equipment.
Finance needs them to weigh capital investments against liquidity
needs. Wouldn't it be great if every
functional team in the organization could share the same, statistically derived, continually updated,
cloud-based demand data?

Fact is, too many organizations still
email spreadsheet updates and manually aggregate inputs from sales teams
based on gut-feel assumptions. Other
organizations rely on Enterprise Resource Planning (ERP) applications or
other transactional databases to inform
their monthly or quarterly Sales and
Operations Planning (S&OP) meetings.
These systems, though highly valuable,
are simply not geared for forecasting
and planning. Truth be told, the manual
and non-statistical processes associated
with both spreadsheets and legacy BI
systems are error-prone, labor-intensive
and generally ineffective for forecasting
and planning.

Predictive to Prescriptive
Accurate demand forecasts underpin
successful planning enterprise-wide,
from sales and marketing to production and inventory. Many data-mature
organizations have already invested
in advanced analytic applications that
bring these two ends of the business
together - sales and operations - in a
unified environment.
Such applications markedly increase
forecast accuracy while automating the
forecast process and slashing labor time.
Some of the higher-end tools also run
optimization algorithms that can effectively prescribe best-actions that take
into account business policies and rules
under virtually infinite sets of parameters, constraints, or business scenarios.
So-called Monte Carlo simulation is one
such technique to what-if test an unlimited number of scenarios to reveal whole
ranges of potential outcomes, including
the probabilities of each. This is the
stuff of not just predictive analytics, but
prescriptive analytics, in which information technology is geared to optimize all
facets of management decision making.
Finally, best-of-breed applications
can also now fully integrate financial
forecasting into the demand-supply

planning process. Done on a rolling
basis, financial integration enables organizations to run truly "evergreen" processes for what many analysts refer to as
integrated business planning (IBP).
The returns on investment in a
well-implemented IBP software platform are numerous and extremely high
in value: lower inventory costs and
improved service levels, reputation,
customer loyalty, cash flow, investment
timing, and top and bottom lines.

Workflow and Knowledge
The last piece of any best-in-class forecasting and planning application is the
ability of knowledge workers to not only
make use of advanced-analytic forecast
tools, but to fine-tune forecasts with
insights only found within the employee
base (not found in the data). This could
include a business user's knowledge of a
new competitor, a forthcoming product
release, an unexpected order, or a cancelled customer contract. It's important to note that any such adjustment
or override capability is matched with
workflow and documentation tools to
automatically track all activities by time,
user and reasoning.
Given the right analytics, automation
tools, and workflow features, organizations investing in cloud-based IBP
should have measurable targets for
streamlined supply chain and fulfillment processes, lower operating costs
and improved customer service and
profit. That's been our experience at
Vanguard Software. Learn more about
Forecasting accuracy by downloading
our whitepaper at http://www.vanguardsw.com/resources-list/roi-promise-forecast-accuracy.
Neal Goffman is the chief sales and marketing
officer for Vanguard Software. He is an analytics
veteran with more than 20 years of domain experience.
Goffman has held strategic leadership roles for organizations including IBM, CIBER and several startups over
his career.

FALL 2017 Supply Chain World

15


http://www.vanguardsw.com/resources-list/roi-promise-forecast-accuracy http://www.vanguardsw.com/resources-list/roi-promise-forecast-accuracy

Table of Contents for the Digital Edition of Supply Chain World - Fall 2017

Contents
Supply Chain World - Fall 2017 - Cover1
Supply Chain World - Fall 2017 - Cover2
Supply Chain World - Fall 2017 - 1
Supply Chain World - Fall 2017 - Contents
Supply Chain World - Fall 2017 - 3
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Supply Chain World - Fall 2017 - Cover3
Supply Chain World - Fall 2017 - Cover4
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