The document provides a checklist for establishing an effective demand planning process. It outlines key steps such as customizing product forecasts, using multivariate analysis, accounting for backlogs, basing inventory decisions on forecasts, generating marketing and supply chain forecasts, continuously monitoring models, creating product-level forecasts, and comparing revenue and demand planning numbers. Taking these steps moves an organization to higher maturity in demand planning.
The Art and Science of Sales Forecasting: A Webinar for Sales Managers and Co...Birst
Overview
Sales forecasting is a science and an art. It is the combination of information and metrics, intuition and best practices. However, sales forecasting is most commonly associated to the standard grading methodology of the particular customer relationship system that is being used (Salesforce.com, Oracle, Microsoft, etc.). In reality, how do key sales leaders become high performing accurate sales forecasters? In addition, how do companies effectively utilize sales forecasting information to increase overall organizational performance?
Here’s what we’ll discuss in this session:
State-of-the-art forecasting strategies, best practices, and key metrics
The interconnection between product complexity, company lifecycle stage, and accurate forecasting
Mitigating downside risk and triangulation strategies to determine the truth
Deal inspection and vetting sales rep forecasts
The different types of sales forecasters; exaggerators, sandbaggers, and Heavy Hitters
The difference between snapshot, intra-department, and inter-department sales forecasting
The Art and Science of Sales Forecasting: A Webinar for Sales Managers and Co...Birst
Overview
Sales forecasting is a science and an art. It is the combination of information and metrics, intuition and best practices. However, sales forecasting is most commonly associated to the standard grading methodology of the particular customer relationship system that is being used (Salesforce.com, Oracle, Microsoft, etc.). In reality, how do key sales leaders become high performing accurate sales forecasters? In addition, how do companies effectively utilize sales forecasting information to increase overall organizational performance?
Here’s what we’ll discuss in this session:
State-of-the-art forecasting strategies, best practices, and key metrics
The interconnection between product complexity, company lifecycle stage, and accurate forecasting
Mitigating downside risk and triangulation strategies to determine the truth
Deal inspection and vetting sales rep forecasts
The different types of sales forecasters; exaggerators, sandbaggers, and Heavy Hitters
The difference between snapshot, intra-department, and inter-department sales forecasting
When it comes to product development, companies have long relied on traditional tools and approaches. By incorporating predictive analytics into the process, organizations can sharpen their forecasts; better predict product performance, failures, and downtime; and generate more value for the business and its customers. Yet doing so requires companies to thoroughly assess their strategic goals, their appetite for investment, and their willingness to experiment.
A case study on how to improve forecast accuracy by incorporating market or business intelligence into statisitical forecasting and know whether it improves forecast accuracy or not.
Business Case: Sales forecasting with SAS Advanced Analytics for the Pharmace...Claudio Menozzi
Goal: Predict New Product Market Penetration
Company: One of the world’s largest biotech companies, with more than 7,000 employees across six continents and a rapidly expanding product portfolio and a growing pipeline.
Business Area: The company provides medical product support across the Hospital Channel
Business Needs: Understanding the adoption of the existing products and predict adoption of new products allows to increase the customer service, adoption and eventually profitability
Project dealt by Achille Masserano, Enterprise Information Manager at Blue BI
Sales & Operations Planning (S&OP): An IntroductionSteelwedge
Do you know the secret to a successful Sales and Operations Planning process?
Your ability to troubleshoot issues, plan for unexpected events, and maintain a reliable, single set of planning numbers is drastically affected by people, process and technology.
Educate your colleagues or refresh your own skills with the new introduction to S&OP presentation.
For more information about S&OP and how Steelwedge can help your business, please visit: http://www.steelwedge.com/resources/sales-and-operations-planning-intro/
This course will help you understand what sales forecasting is and how to select the right forecasting techniques.
Understand what sales forecasting is
Step by step to create a sales forecast
Qualitative and quantitative forecasting methods
Check it out: https://www.experfy.com/training/courses/sales-forecasting
What Great Sales & Operations Planning (S&OP) Feels Like!Steelwedge
Featured Presenter - Tom Wallace, S&OP Author and Educator
Like most manufacturing organizations, you likely have some quantitative measurement goals for your Sales & Operations Planning initiative. But, like the saying goes, it’s not just how it looks (metrics) but importantly, how it feels (organizational impact).
Join Steelwedge and industry educator, author and reknowned S&OP practice leader, Tom Wallace, for a live webinar to test your S&OP “feel factor”. In this interactive session, you will learn examples and ideas for your people, process and technologies to achieve some great feeling S&OP, including:
• Fewer surprises, resolved quickly
• 18+ months of forward visibility
• Enthusiastic engagement of top management and
• Delivering on strategic goals with S&OP
CSCMP 2014: Bayer: Putting the S Back in S&OPAlyssaVallie
Balancing production efficiency and responsiveness to demand has never been more important or more challenging for companies with manufacturing-dominant cultures. Bayer Health Care shares their journey to S&OP excellence and how emphasizing the “S” in S&OP led to the successful redesign of its processes, overcoming ERP shortcomings to align market priorities with manufacturing capacity and extract the maximum competitive advantage from its supply chain.
Supply Chain Risk Management - made easy!Heiko Schwarz
Pressure in terms of innovations and costs as a result of the globalization of markets and services are forcing companies to focus more strongly on international procurement. This globalization, combined with a fall in added value leads to a new, complex risk structure, which necessitates continuous monitoring of various risk potentials along all supply chains.
The Supply Risk Network from riskmethods has been developed to address precisely
these challenges.
When it comes to product development, companies have long relied on traditional tools and approaches. By incorporating predictive analytics into the process, organizations can sharpen their forecasts; better predict product performance, failures, and downtime; and generate more value for the business and its customers. Yet doing so requires companies to thoroughly assess their strategic goals, their appetite for investment, and their willingness to experiment.
A case study on how to improve forecast accuracy by incorporating market or business intelligence into statisitical forecasting and know whether it improves forecast accuracy or not.
Business Case: Sales forecasting with SAS Advanced Analytics for the Pharmace...Claudio Menozzi
Goal: Predict New Product Market Penetration
Company: One of the world’s largest biotech companies, with more than 7,000 employees across six continents and a rapidly expanding product portfolio and a growing pipeline.
Business Area: The company provides medical product support across the Hospital Channel
Business Needs: Understanding the adoption of the existing products and predict adoption of new products allows to increase the customer service, adoption and eventually profitability
Project dealt by Achille Masserano, Enterprise Information Manager at Blue BI
Sales & Operations Planning (S&OP): An IntroductionSteelwedge
Do you know the secret to a successful Sales and Operations Planning process?
Your ability to troubleshoot issues, plan for unexpected events, and maintain a reliable, single set of planning numbers is drastically affected by people, process and technology.
Educate your colleagues or refresh your own skills with the new introduction to S&OP presentation.
For more information about S&OP and how Steelwedge can help your business, please visit: http://www.steelwedge.com/resources/sales-and-operations-planning-intro/
This course will help you understand what sales forecasting is and how to select the right forecasting techniques.
Understand what sales forecasting is
Step by step to create a sales forecast
Qualitative and quantitative forecasting methods
Check it out: https://www.experfy.com/training/courses/sales-forecasting
What Great Sales & Operations Planning (S&OP) Feels Like!Steelwedge
Featured Presenter - Tom Wallace, S&OP Author and Educator
Like most manufacturing organizations, you likely have some quantitative measurement goals for your Sales & Operations Planning initiative. But, like the saying goes, it’s not just how it looks (metrics) but importantly, how it feels (organizational impact).
Join Steelwedge and industry educator, author and reknowned S&OP practice leader, Tom Wallace, for a live webinar to test your S&OP “feel factor”. In this interactive session, you will learn examples and ideas for your people, process and technologies to achieve some great feeling S&OP, including:
• Fewer surprises, resolved quickly
• 18+ months of forward visibility
• Enthusiastic engagement of top management and
• Delivering on strategic goals with S&OP
CSCMP 2014: Bayer: Putting the S Back in S&OPAlyssaVallie
Balancing production efficiency and responsiveness to demand has never been more important or more challenging for companies with manufacturing-dominant cultures. Bayer Health Care shares their journey to S&OP excellence and how emphasizing the “S” in S&OP led to the successful redesign of its processes, overcoming ERP shortcomings to align market priorities with manufacturing capacity and extract the maximum competitive advantage from its supply chain.
Supply Chain Risk Management - made easy!Heiko Schwarz
Pressure in terms of innovations and costs as a result of the globalization of markets and services are forcing companies to focus more strongly on international procurement. This globalization, combined with a fall in added value leads to a new, complex risk structure, which necessitates continuous monitoring of various risk potentials along all supply chains.
The Supply Risk Network from riskmethods has been developed to address precisely
these challenges.
• Make Versus Buy
• Benefit of Outsourcing
• Source of Supplier Information
• Strategis Selection
• Supplier Relationship Management (SRM)
• Industry Example
Demand Forecasting, undeniably, is the single most
important component of any organizations Supply Chain. It
determines the estimated demand for the future and sets the level
of preparedness that is required on the supply side to match the
demand. It goes without saying that if an organization doesnt get
its forecasting accurate to a reasonable level, the whole supply
chain gets affected. Understandably, Over/Under forecasting has
deteriorating impact on any organizations Supply Chain and
thereby on P and L. Having ascertained the importance of De-
mand Forecasting, it is only fair to discuss about the forecasting
techniques which are used to predict the future values of demand.
The input that goes in and the modeling engine which it goes
through are equally important in generating the correct forecasts
and determining the Forecast Accuracy. Here, we present a very
unique model that not only pre-processes the input data, but
also ensembles the output of two parallel advanced forecasting
engines which uses state-of-the-art Machine Learning algorithms
and Time-Series algorithms to generate future forecasts. Our
technique uses data-driven statistical techniques to clean the data
of any potential errors or outliers and impute missing values if
any. Once the forecast is generated, it is post processed with
Seasonality and Trend corrections, if required.Since the final
forecast is the result of statistically pre-validated ensemble of
multiple models, the forecasts are stable and accuracy variation
is very minimal across periods and forecast horizons. Hence it
is better at estimating the future demand than the conventional
techniques.
Inventory Decisions Sensitive To Demand And Lead Times In The Supply ChainaNumak & Company
Due to global competition, demand is no longer fully determined in any business area. The environment today is extremely dynamic. In such a situation, an estimation error anywhere in the supply chain is felt throughout the process. For this reason, forecasting has a very important place in supply chain management.
Integrating A.I. and Machine Learning with your Demand ForecastSteve Sager
There is a paradigm shift in the way companies forecast demand. Learn how you can leverage advanced machine learning to understand how business drivers outside your walls will impact enterprise data.
Sales and Operations Planning (S&OP) OverviewMichael Ryan
Improved revenues, business performance, and customer satisfactions are outcomes of a strong Sales and Operations Planning (S&OP) process.
S&OP can be applied to a variety of industries, from cosmetics to aftermarket parts manufacturers.
Demand Planning Leadership Exchange: Demand Sensing - Are You Ready? Plan4Demand
866-P4D-INFO | info@plan4demand.com | www.plan4demand.com
Gary Griffith and Joel Argo combine over 25 years of statistical forecasting experience to discuss the capabilities of Demand Sensing, what it is and what it isn’t, how this near-term forecasting method integrates with your mid to long term forecasts, and tips to shift pragmatically towards a demand-driven culture in your organization.
This session will cover key things to consider when approaching the concept of Demand Sensing in your organization, when and who should use it, and how it fits within different business scenarios.
Key take-a-ways include:
• Understanding of key concepts, capabilities & business benefits
• Overview of Demand Sensing technology considerations & system integration points
• Typical data requirements & modeling techniques
• How this next generation technique may be a fit for your organization
Is your organization ready to reap the benefits of Demand Sensing?
Creating a Monetization Framework For Your BusinessBluLogix
There’s little dispute that digital transformation has affected nearly every aspect of B2B commercial activity. Success in the digital economy requires that organizations move beyond traditional ways of doing business while accelerating market-facing responsiveness across all functional areas.
Creating a Monetization Framework For Your Business
Demand_Planning_Process
1. The Ultimate
Checklist for the
Best in Class Demand
Planning Process
A
re you interested in enhancing profitability for a given channel, a product or the
overall enterprise? In that case, one of the important things that you might need is
an effective demand planning system. An effective system for demand planning can
help businesses improve accuracy of revenue forecasts and align inventory levels with the
crests and troughs of demand.
Creating a Demand Planning checklist is an important step in the process of producing a
best-in-class business process. Reality is harsher than one’s imagination, and therefore
the items in this checklist represent your organisation’s maturity level in the whole demand
planning process. The more items you have checked off, the higher is your maturity in
demand planning process.
By Alagiri Samy, Solution Manager, Supply Chain Solution,
BRIDGEi2i Analytics Solutions
Strategy
About the Author
Solution Manager for Supply Chain Solution
forBRIDGEi2iAnalyticsSolutions.Consults
Fortune 500 global firms across industries
to monetise value from Analytics by
analysing information, deriving actionable
insights and delivering sustained impact
through operationalisation of Analytics.
Former Editor in chief for MAARS India.
Recognised as one of the top 180 bloggers
in the field of Big Data & Analytics by Data
Science Central.
27 digiMag
2. Customised Product Forecasts
All products are not the same; they exist within the breadth
of long to short life cycle, costs (low to high) and many
others. And therefore during forecasting each one has to be
treated differently based on their type. So, it is quintessential
to build an improved model with customisation at product
and geographic level as it will improve the forecast accuracy
manifolds and provide improved insights in the future.
Multivariate Improved Product Forecasts
Forecasting involves estimating future values for a process
that is least controllable. Examples range from policy changes
in country to weather and stock price performance. And so
forecasting of a product based on the previous demand that
the product saw over a period of time is just not enough, as
there are multiple other factors that also affects the demand.
In this case, to counter the external changes, enterprises
should build an improved multivariate product level model and
this would give a holistic view of the demand.
Demand Forecasting based on Backlogs
Demand forecast based on backlogs would be a key step in
building the best-of-breed forecasting model. Forecasting
model that has been built will include different types of
backlogs as one of the parameters while providing the demand
numbers. This step will help demand planners combat the
internal factors that will affect the supply and demand.
Inventory Holding Decisions Based on Forecasts
Following this key step, enterprises are slowly moving from a
tactical mode to operational mode. That is, enterprises would
start looking at this numbers as sacrosanct numbers and
would start religiously using this in their day-to-day operations.
This would be a great milestone in this process. Inventory
levels would be decided based on the model suggestions
and the accuracy of results would be periodically measured to
validate the process.
Marketing Forecast
Is your marketing team reporting the demand forecast
numbers on a regular basis? Generating these numbers is
the first step towards a Himalayan task of building a robust
demand planning system. Not everyone can predict the future,
but if one wants to be able to predict right and sell everything,
then anticipating forecasts is the key.These numbers have the
potential to give you a picture of the market’s capacity and
will be a good heads-up for starting your demand planning
process.
Supply Chain Forecasts
Marketing forecast is good but what is more important is an
in-home supply chain demand forecast. Every Supply Chain
organisation should have a model that provides the forecast
numbers based on the functioning of supply chain process.
With increasing competition and volatile business macro-
economy, the demands are no longer certain. Thus, modern
enterprises have come to realise that meeting demand with
supply after understanding demand and planning definitely
pays off. But if the forecasts are wrong, then there will be
a negative cascading effect that will be felt throughout the
organisation.
Continuous Model Monitoring
Changing Data format, evolving business environments,
transforming business objectives makes the model wither
and therefore, it is not fair to expect a good performance
consistently. With these changes, the models will have
to adapt and evolve over time. Therefore, it is of utmost
importance that the model is being continuously monitored
and tweaked based on the circumstances and rising need.
Product Level Forecasts
There are demand numbers at an overall organisation level
but do you have the demand numbers at a product level?
Numbers based on geography and product level will enable
the demand planners to plan cautiously and efficiently.
For example, product group level forecasts are needed in
budgeting and forecast by region and products are needed
for logistic decisions and many others. Product level forecast
is the first milestone in the whole demand planning process
as it shifts gears from strategic to a tactical demand planning
process.
Comparison of Revenue Planning and Demand Planning Numbers
The last and final set of steps would be comparing the demand planning numbers. A modern enterprise would build a dashboard which
will combine both these numbers. The dashboard would provide:
• Improved reporting at all the levels of the organisation
• Better measurements and metrics
• Monitoring of demand forecasts at multiple levels
• Validate forecast numbers with performance
Working on the checklist takes an organisation from one maturity level to other and also provides a competitive advantage.
Do not worry, if you think, you have not started off. After all, “a journey of thousand miles begins with a single step”.
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