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Overview of SAS for Demand-Driven Planning and Optimization

December 1, 2019


Overview of SAS for Demand-Driven Planning
and Optimization. Today, businesses around the world face many
challenges, including globalization pressures, supply chain complexities, rising customer
demands, the need to increase revenues across global markets, and lower costs. Adding to these challenges is the economy,
in which supply has outstripped demand for the past several years. Organizations invest significantly to bring
their products to market. During this process, organizations make many assumptions about
how much revenue and profit a product will generate. One of the assumptions is that the
right product will be delivered at the right place, at the right time. If an organization can achieve this simple
goal, there is a good chance that it will also achieve its overall revenue and profitability
goals. Organizations use metrics such as inventory
costs, inventory turns, expediting costs, and service levels to determine whether they
are on track to meet their goals. The most critical functions in supply chains are planning for supply and demand. If you get the demand plan right, you increase
the potential for getting everything else right in the supply chain. Unfortunately, many companies struggle in
this area. The cost of poor forecasting and planning
can be quite high. Over-forecasting a product can lead to excess
inventory and margin erosion. Under-forecasting can result in lost sales
and customer dissatisfaction. However, SAS for Demand-Driven Planning and
Optimization helps you overcome all these challenges in supply chain planning. The SAS
for Demand-Driven Planning and Optimization suite consists of SAS Forecast Analyst Workbench,
SAS Inventory Optimization Workbench, SAS Collaboration Planning Workbench, and SAS
Demand Signal Analytics. With the ability to automatically create the
most accurate statistical baseline forecast, you can sense and shape demand at all levels
of the product hierarchy. If a new product is in your portfolio, you
can use the patented new product forecasting process, called Structured Judgment, to find products that are very similar to that new product. These similar products are known as “act-like” products. After you find similar products, you use a
combination of data mining, segmentation and clustering, statistical forecasting, and domain knowledge to accurately predict new product launches. To optimize planning and efficiency, you can
use collaborative planning. Collaborating with stakeholders enables you
to combine statistical forecast information with domain knowledge in order to construct
the most accurate consensus plan. SAS for Demand-Driven Planning and Optimization
also helps you combine the demand forecast and the inventory optimization across a multi-echelon
distribution network. The result is lower inventories with increased
customer service levels. During this process, you can perform supply
shaping or “What-if” scenario analysis. Finally, you can obtain a holistic view of
all information that is related to demand and planning by tracking customer behavior,
new product launches, and social media feedback. This knowledge can help you drive better decision
making across the supply chain network. Let us look at SAS Forecast Analyst Workbench,
which is part of SAS for Demand-Driven Planning and Optimization. You can see that SAS Forecast Analyst Workbench
enables you to create forecasts that are highly scalable and flexible. You create forecasts that contain large numbers
of time series and that use different types of key performance indicators. SAS Forecast Analyst Workbench automatically
selects the model that is most suitable for the time series, and then generates the forecasted
values. You can also specify statistical parameters. You can reconcile the predicted values up
or down the business hierarchy to ensure that the forecasts are evenly balanced. You can also use the advanced statistical
capabilities of SAS Forecast Studio to better predict and sense the demand. The New Products workspace in SAS Forecast
Analyst Workbench uses the patented structured judgment process, which combines data mining,
clustering, and statistical forecasting with domain knowledge in a structured way. The workspace predicts the future demand of
new products by using the act-like products or surrogate products that you specified in
the product profile, including attributes and characteristics. Finally, you can integrate the new product
forecasts into the planning process in order to optimize your planning strategy. Next, let us see the details of SAS Collaborative
Planning Workbench. This solution provides consensus reconciliation
up or down the business hierarchy. The configurable workflow and approval process
that are integrated with email provide an easy way for all stakeholders within your
organization to collaborate seamlessly. Stakeholders, including sales, marketing,
and finance personnel, can use domain knowledge and business judgment to review the unconstrained
baseline demand and to provide inputs. Stakeholders can use Microsoft Excel spreadsheets
to collaborate. Finally, planners can easily review and override
forecasts at any level in the hierarchy and can instantly see the overall impact across
geographies, markets, and channels. SAS Inventory Optimization Workbench calculates
optimal inventory levels, using inventory policy parameters throughout the supply chain. This solution uses the forecast to automatically
calculate the optimized inventory levels and the order quantities for all SKUs at every
level and location within the supply chain network. Analysts can sense and shape supply across
the supply chain network by using a what-if analysis. Finally, SAS Inventory Optimization Workbench
helps analysts and buyers maintain adequate stock levels, maximize response time, and
improve customer satisfaction. SAS Demand Signal Analytics contains a user-friendly
and powerful in-memory, visual, and analytic approach to analyze demand data. You can analyze demand patterns, and you can
gain insights into sales, shipments, pricing, promotions, and operational performance. This video showed you how the solutions that
are part of SAS for Demand-Driven Planning and Optimization can help organizations achieve
goals, such as: Sensing demand signals that are generated by
changes in the marketplace. Rapidly aligning the supply chain to fluctuations
in demand, and aligning demand and supply in order to improve
customer service. SAS for Demand-Driven Planning and Optimization
is an integrated planning suite that delivers a more accurate demand forecast, a structured
process, collaborative planning, visualization, and advanced analytics and optimization. SAS for Demand-Driven Planning and Optimization
is best suited for demand planners, forecast analysts, inventory analysts, buyers, and
business users, such as sales account managers, business analysts, finance analysts, and executives. For more information about SAS for Demand-Driven
Planning and Optimization, go to www.sas.com.

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1 Comment

  • Reply Kevin Graham April 15, 2016 at 8:29 pm

    This is a high quality video that highlights SAS for Demand-Driven Planning and Optimization (DDPO), as an "integrated planning suite that delivers a more accurate demand forecast, a structured process, collaborative planning, visualization and advanced analytics and optimization…" all from the advanced analytics market leader, SAS Institute.

    Please forward to a colleague.

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