The Challenge:
This company is a diversified distributor and marketer of a wide range of small appliances for use in and outside the home. It markets products under licensed brand names, company-owned brand names, and private label brand names primarily in North America, Latin America and the Caribbean.
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- Need to Provide Forecasting Foundation. Short customer order lead-times with long manufacturing/sourcing lead-times dictate a make-to-stock environment, thereby creating dependence on reasonable forecast accuracy. Their Field Sales
resources were responsible for this crucial estimate of demand that drives production requirements, without a standardized forecast methodology or statistical forecasts.
- Need to Account for 'Causal Factors'. Promotions and other factors that significantly increased or decreased demand were not captured within the forecast solution, requiring the user to remember these events when manually creating the forecast.
- Need to Improve Forecast Accountability. Forecast accuracy was managed on an ad-hoc basis using manual analysis to generate forecast reports. Forecast
reports were not directly tied to each Field Sales
resource resulting in aggregate forecasts with no
individual accountability.
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Inaccurate forecasts resulted in lower order fill-rates, additional inbound and outbound expedited freight costs, vendor compliance penalties, excess inventory for most items, and reactive focus of Field Sales and Supply Chain resources. When factoring these explicit costs as well as subsequent account management issues, it became obvious ' a new solution was needed.
The Approach:
This client partnered with Auxis Management & Technology Solutions (Auxis) to select and implement a new IT infrastructure based on business strategy, future state processes and business requirements. Auxis developed a quantitative business case for improving forecast accuracy as a part of the overall core systems replacement and operational improvement business case known as 'Vision '05'. The team conducted a thorough evaluation of forecast solutions and selected Demantra Spectrum TM due to its fit with the envisioned process and forecast requirements.
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- Statistical Forecast Foundation. Given historical
demand patterns, the Demantra Demand Planning
engine generates statistical forecasting using a
Bayesian Method to blend multiple forecast algorithms.
The statistical forecast includes a seasonality and trend
component, thereby eliminating the need to manually
estimate these variables. In addition, the system
generates forecasts from Point-of-Sale data to estimate
end-consumer demand with visibility to retail inventory,
not just retail customer demand (orders and
shipments).
- Inclusion of 'Causal Factors'. Demand is influenced by
planned and unplanned circumstances. The forecast
solution captures historical and future promotions to
account for promotional lift. In addition, the system
allows the historical demand to be adjusted when
historical anomalies occurs. Thus, statistical forecasts
will be generated from 'meaningful' history.
- Drive Budgeting and Longer-Term Planning. Sales
Resources create and manage forecasts by account
by item for a rolling 78 week timeframe. The solution
has been implemented with a roll-up by the Sales
Hierarchy as well as the Product Hierarchy; thus, Sales,
Marketing and senior management have visibility to
the financial direction of the business. Additionally, a
sales budget is created with this forecast foundation on
an annual basis. The budget defines sales objectives
and is used to compare actual performance to plan.
- Formal Process with Forecast Accuracy Reporting. The
forecast process was redesigned with more structure, a
keen focus on exception management and enhanced forecast reporting that can be summarized by account and by the forecast owners.
- Automated Inbound and Outbound Integration. Auxis managed the implementation and developed a closed-loop integration to systematically load demand history, pricing and master file data into the forecast solution, and then export the approved forecasts to the planning system.
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The Results:
Manufacturing and distribution companies know that
accurate forecasts have a direct impact to the bottom line
and long-term account relationships. For this client the result
of implementing the forecast solution streamlined the
business process and created a bottom line, cascading
effect throughout the organization.
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- Increased Order Fill-Rates. The most challenging
component of inventory management is estimating
demand. With increased forecast accuracy, the right
products are in stock at the right time, resulting in
improved order fill rates.
- Reduced Overall Inventory. With more accurate
forecasts, less safety stock is required to account for
demand variability. Excess inventory is reduced with
formal forecast measurement and statistically-based
forecasts.
- Improved Sales. A direct consequence of increasing
fill-rates is increased revenue. As a secondary, long-term
benefit to superior fulfillment performance,
opportunities become available to gain distribution for
additional products.
- Cost Savings. Increased forecast and planning
accuracy reduces the need to expedite inbound and
outbound freight. In addition, there are lower vendor
compliance penalties. Finally, the organization is able
to provide additional focus on sales and planning
activities rather than reacting to fulfillment issues.
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About Auxis
Auxis is a management consulting and outsourcing firm dedicated to enabling growth for our customers. We offer a multi-disciplined approach to develop and implement practical, robust and scalable solutions that generate superior business performance, providing significant competitive advantages to our clients. Our core belief is that our success should be measured by tangible and sustainable financial results. Simply put, Auxis helps clients prosper. |
