Archive for the ‘demand planning training’ Category

Demand Planning Tutorial July 7-8 Boston, MA

Sunday, June 27th, 2010

Demand Planning and Forecasting Tutorial – 2-Day Interactive Training.

July 7-8, 2010 Norwood, MA at the Four Points by Sheraton Hotel.

Workshop is conducted on Wednesday and Thursday,  so you can spend the Spring weekend in gorgeous Boston, MA or see the yachts on the Charles River!

Whether you are new to demand forecasting, or a seasoned pro looking to enhance your knowledge, you cannot afford to miss this opportunity.  We will answer questions such as:

  1. Do you trust the power of Statistical models to form a clean baseline forecast?
  2. When does a forecast actually become a demand plan?
  3. What do you use to create the demand history – shipments or Forecasts?
  4. What is the right software to plan your demand?
  5. Do you model and forecast every item every month?

GET SKILLS YOU CAN USE AT WORK

You will learn to…

  • Set up a Demand Planning Process for your business
  • Clean your data and adjust for data anomalies
  • Use Statistical modeling to create baseline forecasts
  • Use exponential smoothing and linear regression models
  • Leverage the Regression capabilities in Excel
  • Incorporate promotional events into your forecast modeling
  • Use Forecast Error as a diagnostic to improve model quality
  • Reconcile the top-down category forecast and the Bottom-up SKU level Demand Plan.

We will explain the modeling methodology and process behind accurate demand forecasts and how to effectively use promotional information to arrive at a consensus forecast. The focus will be on demand modeling using statistical techniques, the methodology to perform model diagnostics, forecast accuracy measurement and the process to incorporate market intelligence.

LEARN FROM INDUSTRY EXPERTS

Each training day will also include an industry-specific presentation from a senior supply chain manager:

NETWORK WITH YOUR PEERS

You will have ample opportunity to meet, interact, and learn from other demand planning professionals with team challenges and networking exercises.

ADD TO YOUR CREDENTIALS

Upon completion of the tutorial, you will be awarded a certificate of completion from Demand Planning LLC, attesting to your newly-acquired skills in Demand Planning.

Price is $1,045.  Please call the Demand Planning LLC office for a special room package subject to availability.

REGISTER NOW ON DEMAND PLANNING.NET!

Event URL: http://www.demandplanning.net/demandplanning_tutorialNJ.htm
Registration URL: http://www.demandplanning.net/seminar_anregistrations.php
Event brochure: http://www.demandplanning.net/documents/dpTutorial_NJ_w.pdf

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Using Orders to predict POS?!

Wednesday, December 16th, 2009

I saw this linked in comment in a discussion group:

“I hate to get technical”. That expression always bothered me, but I am wondering who IS getting technical….who is using Orders to help predict POS? Who is using a “day of the week” dummy variable?
It is my belief that the current simplistic solutions aren’t able to deal with issues like this. Let me explain why….because they can’t solve the technical modeling issues to solve the problem correctly. I defy someone to tell me TWO solutions that can bring in orders to help forecast POS demand and identify and adjust the model based on the lead/lag relationship between orders and POS demand. The same holds true for “day of the week” dummy variable added in automatically when you have daily data. Also “week of the year”….”day of the month(when appropriate)”….fridays before a WEEKEND holiday…do you see my point?….. I could go on all day here…..How about Interventions?….identifying and adjusting the model for a “level shift”….”local time trend”….the challenge has made…..one more thought….the conclusion from the M3 competition that simpler was better did have a lot to do with the “KISS methodology” conclusion which didn’t necessarily help besides the technical difficulty.

“”I hate to get technical”. That expression always bothered me, but I am wondering who IS getting technical….who is using Orders to help predict POS? Who is using a “day of the week” dummy variable?

It is my belief that the current simplistic solutions aren’t able to deal with issues like this. Let me explain why….because they can’t solve the technical modeling issues to solve the problem correctly. I defy someone to tell me TWO solutions that can bring in orders to help forecast POS demand and identify and adjust the model based on the lead/lag relationship between orders and POS demand. The same holds true for “day of the week” dummy variable added in automatically when you have daily data. Also “week of the year”….”day of the month(when appropriate)”….fridays before a WEEKEND holiday…do you see my point?….. I could go on all day here…..How about Interventions?….identifying and adjusting the model for a “level shift”….”local time trend”….the challenge has made…..one more thought….the conclusion from the M3 competition that simpler was better did have a lot to do with the “KISS methodology” conclusion which didn’t necessarily help besides the technical difficulty.”

I was initially puzzled by the order of the POS versus orders – what is forecasting what?  or even Why?  Is it useful to predict POS using the orders?  Even if there is a significance, would that be a spurious variable just proxying inefficiently for the inventory levels and perhaps promotional activity?

We have always tried to solve client problems that needed the POS data to try to predict the orders.  Now you mention using Orders to predict POS, which seems to be a novel idea.

Orders can predict POS?  If so, how?  If I am the retailer and I can place orders, how will I use my historical order pattern to predict what my consumer is going to buy?

Perhaps just use the old adage “stack ‘em high and see ‘em fly”?!

Just order from the manufacturer and build your shelves and stores with the inventory, so the mere visibility of this inventory creates POS demand?!  If so, this will make the push concept very usable.  Seems very consistent with the supply side argument of the economists on the monetarist side.

It is good to see a refreshing view amidst all the supply chain forecasters subscribing to the pull-based forecasting methodolgy.  And I am one of them too……. I believe that using the POS can better predict Orders, the opposite of what you are proposing.

And this is what we preach and educate to our constituents.  How to better use your POS demand and inventory patterns to better create an order forecast.

You may want to review our web workshop information at

http://www.demandplanning.net/cpg-demand-planning-web-workshop.htm.

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Excellent participation in the Forecasting Tutorial

Tuesday, November 3rd, 2009

The forecasting workshop on Oct 22 and 23 held at Whippany, NJ was well attended by companies from different industries from Consumer goods, to medical devices to Technology companies. We had participants from

  • SMSC
  • J&J
  • Tools Group
  • Bush Brothers
  • Merck
  • Crabtree and Evelyn
  • Avon Products
  • Niles Audio

Thanks to the great audience, the workshop was very interactive with people talking about their real world planning experiences and comparing notes on how they dealt with specific situations.  A number of questions were addressed during this interactive forum.  I truly enjoyed the participation and nothing better than conducting a workshop with an engaging audience.  Thank you.

The major focus on the first day was forecasting in the current economy.  There was a lot of discussion on the V-shaped recovery and how to forecast for it.  Although exponential smoothing is an adaptive technique that normally catches up with a lag, it is difficult when the demand suddenly drops and then sharply recovers a few months later.  We all discussed the importance of scenario planning and other techniques that are important like leading indicators.

The guest speakers Mark Temkin and Jay Nearnberg also provided valuable insights to the group.  There was discussion on inventory optimization, S&OP and demand metrics.  There were number of questions on modeling and metrics, particularly the usage of MAPE and the methodology to compute the MAPE.  The weighted Mean Absolute Percent Error seemed to be the most common performance metric used by most organizations, although some had used a variation of it.

Please feel free to post any follow-up questions on this workshop either here or in our Linked-In Group for DemandPlanning Net Training.

Mark Chockalingam

Woburn, MA

November 3, 2009.

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