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Value Chain Planning-The Business Plan or the annual Budget often follows the following outline:
Capacity and other bottlenecks
Organizational Consensus
Revisions to Spend and volumes
Management buy-in
Internal Factors.
Development of a Sales and Marketing Plan
Calendar Monthly forecast
Strategic analysis of external factors:
- Economic
- Political
- Competitive
Operating Budget
- Manufacturing Costs
- Administrative costs
- Sales and Marketing Overheads
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Value Chain Planning - Exception Management
Budget Shortfall Review- Depending on the pain points of the current organizational process, we design this meeting to reconcile top-down financial and marketing forecasts with the operational demand plan. The GAP identification and resolution is a major part of the Sales and Operations Planning Process
Exception Management- A well-defined process will thrive on exception management. All Component meetings will start with a follow-up of issues from the previous meeting and deal with exception issues highlighted by the meeting templates. A concise design of meeting templates will help you achieve brief, sharply focused, effective meetings
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Value Chain Planning -The Business Plan
Valtitude has developed a unique methodology to develop long-term forecasting and analyzing the forecast sensitivity.
Often the annual Marketing Plan is the driver for the demand information in the annual budget. The Marketing Plan is developed with a volume forecast for the year along with the spend levels necessary to create and sustain the expected demand for the products. The process for Market share forecasting is explained here. Marketing-mix modeling is a key component of developing the Marketing Plan. The Business Plan or the annual Budget often follows the following outline:
Capacity and other bottlenecks
Organizational Consensus
Revisions to Spend and volumes
Management buy-in
Internal Factors.
Development of a Sales and Marketing Plan
Calendar Monthly forecast
Strategic analysis of external factors:
- Economic
- Political
- Competitive
Operating Budget
- Manufacturing Costs
- Administrative costs
- Sales and Marketing Overheads
To know More, Visit Us:
#demand planning#forecasting consulting#valuechainplanning#consulting services#supply chain management#mape#forecasting#Valtitude#Demand Planning#S&OP Forecasting Consulting#Supply Chain Management Software#IBP#Supply Chain Optimization#sales and operations planning#S&OP process#Operations Planning Process#demand planning solutions#model tuning#forecast classification#Demand Planning LLC#Sales and Operations Planning
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Demand Planning -Incentive Alignment using Metrics
How to measure the Demand Chain?
Financial Forecast versus Demand Plan
How to measure the Supply Chain?
Alternative control metrics
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Value Chain Planning -Top-Down forecasting
In Top-Down forecasting, the forecasts are developed at the brand, category or division level, and then allocated down to the lower levels (to SKU, then to SKU/Warehouse).
There are different schools of thought, arguing that either method is superior. One approach says that forecasting at the detail level results in a much more accurate forecast because information at the detail level is more precise. Aggregating this detailed forecast with a time series of prices produces a realistic view of the financial plan.
The alternate view, which is equally plausible and fair, states that forecasting at the SKU level produces too much noise. At the SKU level, volumes could be very light; some of
the SKUs could be shipped very infrequently. So the lower the level, the more difficult it becomes to create any useful statistical model because of sketchy and intermittent demand data. If that is the case, forecasting at the SKU/customer level will magnify the impact of noise and data infrequency. Forecasting at the customer SKU level also means aggregating not only at the customer SKU to the SKU level, but also aggregating all the way to the top, to the division level.
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Value Chain Planning -Converting Date formats in SAS
Converting Date formats in SAS
SAS is very helpful but can be complex as well. Because of the flexibility it offers, it has to be necessarily complex. The manuals from the Institute are not very comprehensive to cover the length and breadth of the complexity.
How to converts dates and times into the combination format date time? Extracting dates and times out of a date time format is easy. We can use the function date part() and time part() on the date time value and write them as specific formats in the output dataset.
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Value Chain Planning -Training Requirement
Training Requirement
A total of twenty hours of blended learning including (classroom and online e-learning modules) as follows:
Successful completion of the two-day workshop on Demand Planning and Sales Forecasting currently offered as an in-person workshop in various locations
Successful completion of four online modules.
The above two requirements qualify a candidate to sit for the final certification exam. The exam is four hours long and administered in two parts on the same day. Each part will count towards a 50% weight.
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Demand Planning - Forecast Performance Metrics
Mean Absolute Percent Error
Forecast Bias
What do we learn from forecast errors?
Introduction to Exceptions Management
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Demand Planning -Modeling special cases of Demand Product Life Cycle & Long-term Planning
Product Lifecycle and trend • Launch Forecasting • Volume effect on line extension
Event Modeling Baseline vs. Incremental • Illustration of Event Models
Planning for Intermittent Demand What is Intermittent Demand & what causes it? Strategies to handle intermittent demand & Statistical Models for Intermittent Demand
Higher-order Models
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Value Chain Planning -ABF collaboration Model
The ABF collaboration Model leverages consumption and inventory data from the customer and uses a statistical engine to come up with the customer level demand forecasts. The major advantage the ABF process is it enables flexible supply chain planning because of the visibility of customer-level demand.
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Value Chain Planning - VMI and CMI - The Challenge
The traditional continuous replenishment process (CRP) activity does not truly generate a demand plan that can be integrated into the manufacturer’s Supply Chain for production planning purposes.
It can be too tactical and short-term oriented and typically focuses on the next two to four weeks.
The emphasis on order placement and replenishment based on near term activity can be considered a challenge.
Although VMI and CMI are constrained by criticisms of short-term focused and being too tactical, in practice they have been very popular because of their low cost to implement. The key is to leverage low-cost implementation while driving consensus and collaboration and bringing the focus on promotional planning and management.
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Value Chain Planning-Long-term forecasting and analyzing the forecast sensitivity.
Valtitude has developed a unique methodology to develop long-term forecasting and analyzing the forecast sensitivity.
Often the annual Marketing Plan is the driver for the demand information in the annual budget. The Marketing Plan is developed with a volume forecast for the year along with the spend levels necessary to create and sustain the expected demand for the products.
The process for Market share forecasting is explained here. Marketing-mix modeling is a key component of developing the Marketing Plan.
To know More, Visit Us:
#demand planning#forecasting consulting#valuechainplanning#consulting services#supply chain management#mape#forecasting#Valtitude#Demand Planning#S&OP Forecasting Consulting#Supply Chain Management Software#IBP#Supply Chain Optimization#sales and operations planning#S&OP process#Operations Planning Process#demand planning solutions#model tuning#forecast classification#Demand Planning LLC#Sales and Operations Planning
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Value Chain Planning -Supply Collaboration Process-
Once a consensus demand forecast is finalized, Supply planners will refresh their planning systems to arrive at their new schedule with constraints. The new demand may point to imbalances in their supply process including issues in raw materials, finished goods inventory, manufacturing schedule, and capacity constraints.
The collaboration process should consider these issues to problem solve and decide a set of supply constraints to be acted on in the Operations Review meeting.
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Value Chain Planning -Business Planning and Budgeting
Business planning is critical for every company. Often conducted as an annual exercise the business plan is the volume, cost and profit plan for the upcoming year. This is also referred to as the annual budgeting process.
Some companies conduct this as part of the long-range forecasting process, which cover anywhere from three to seven years. The long-term forecasting is indispensable for companies with longer product development cycles. It provides the inputs for capacity planning and other long-term expansion initiatives.
It is common knowledge that longer-term forecasts are more erroneous than short-term forecasts. There are more dynamic variables and error processes at play in determining the conditions expected to prevail in the future. So it is necessary to subject your forecast to a sensitivity analysis to understand the robustness of the forecast.
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Demand Planning -Inventory Metrics
Inventory Metrics
Inventory Turns – Productivity
Dead and Obsolete – The Slobs
Effects of Demand Volatility
Is MAPE a questionable measure?
Incentivizing Demand Planners
Identifying forecast Bias when there is persistent volatility
Demand Management
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Value Chain Planning -Bottom-up/Top-Down forecasting
Adding more excitement to this menu of terminology, different software tools have different methodologies to perform forecast reconciliation between the different levels of forecast. Typically, forecast reconciliation is sought after in cases where you need to forecast multiple levels of the product hierarchy, so in some sense it’s aligned with product grouping and product hierarchy. If you are also forecasting at the customer level, then the levels of aggregation multiply by the customer dimension. Customers may roll up into a sales territory, sales district, and sales region to the national level. In this article, we are going to limit ourselves to illustrating forecast aggregation and disaggregation just using the product hierarchy. We would abstract away from further disaggregation at the customer SKU level.
When you develop your forecasting process, you have a choice to make – at what level do you develop the forecast? You could forecast at SKU level or slightly higher (at brand or sub-brand level) or, given a simpler supply chain you could get away with forecasting at the category or division level.
When forecasting for the supply chain, as a general rule, you forecast at the SKU level. When you have a process focused on this type of detailed forecasting, you could aggregate an SKU level forecast to a higher level forecast, dollarize it, and use it for financial planning, which is the typical methodology for Bottom-up forecasting.
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