Moving the ROC to forecast…….

January 6th, 2012 by Dr. Chockalingam

We hear quite often, that forecasting is a waste of time.  People often cite the weatherman and laugh at forecasts and forecasting as a productive process.

As long as you don’t leave your demand forecasting to the weather man, I believe we can do very well.  Most supply chain problems originate by ignoring the forecasting that is happening through out the organization. In a survey I remember reading a couple of years ago, on average 50% of the people in an organization were forecasting something or other.

If the forecasting process is bad, fix it! You ignore and move on at your own peril!

It is simply impossible to ignore the forecasts, because the ROC (Rest of the Company) is hard at work forecasting something or other.
Even folks in manufacturing who can badmouth forecasting may be using an average run rate of some sort to determine their inventory calculations.  This run-rate determination is actually a forecast, the average, although they think it is no forecast.

If there is a reasonably good demand planning process installed in any organization, we can establish this will easily beat out the “run-rate” or any other average hands down.

A good demand planning process does not just rely on statistical modeling.  It leverages the information from the various players in the rest of the company.  My good friend and my manager at Schering Plough coined the term ROC – Rest of the Company.

The ROC has information.

The ROC also forecasts.

ROC forecasts for different purposes.

For us demand planners focused on the supply chain and mired in the daily fires of the live order stream and its deployment, we only think of the supply chain plan as our reality.   We wonder what does the ROC do other than feeding us some useful info to make the widgets we need to demand plan and produce.

Inventory is a problem but is only one of many problems!

Organizations have a variety of challenges and constraints to solve so they can thrive and grow. Organizations need to plan for the medium to long-term and manage the business accordingly.  At least 50% of the ROC forecasts but NOT necessarily for inventory purposes.

Senior management needs to forecast an EPS for investors and need to hit it within a reasonable threshold. Companies need a long-term forecast to assess what they need in capital investment and where and how to build the facilities for expansion. Even HR needs a forecast.

Thinking every function will be forecasting for the supply chain is like the Dilbert Cartoon “Sure – I will drop everything else and will focus on your problem.”

So forecasting and planning is embedded in various functions and various forms through out the organization and is unavoidable. You cannot tell people it is a real problem so they should stop it! The key is how to leverage the forecasting responsibility and accountability already installed into a holistic process that can let you piggy back and obtain a supply chain forecast for your short-term and long-term planning.

Ignoring the corporate forecasting machine and creating an isolated forecast or an inventory deployment algorithm is a sure way to significant troubles – what we at Demand Planning LLC caution as the fragmented planning process or the lack of the often glorified “S&OP” process.

So in summary, there is no issue with the ROC or 50% of the ROC involved in forecasting.  The real problem is when supply chain decides to ignore the forecast or the forecasting process that is already etched in the ROC(k) and decide to move on in isolation.

Demand Planning LLC does use and recommend advanced algorithms for demand forecasting and leveraging customer input.  But that is only half our story.

We work with Sales, Marketing, Supply chain and Senior management to drive a holistic process to leverage demand information and build forecasting processes that are used across most of the organization.

We salute the hero who decides to use a demand forecast that is only 50% accurate rather than ignoring or side-stepping the forecast.  Accuracy of the forecast is secondary.

Start with the forecast first and make plans and contingencies for the extent of the error.   Improve on the forecast by quizzing, dialoguing, negotiating and working with the ROC.  This should be well emphasized in the basics of supply chain management.

Join hands together to move the ROC to make a better demand plan!

Questions on Demand Planning Training Workshop in India

December 13th, 2011 by Dr. Chockalingam

In response to our workshop announcement, we have received several emails with number of questions.  Given that we have only experienced the tip of the iceberg when it comes to demand planning and supply chain careers in India, the opportunity set is explosive for a knowledgeable and skilled demand planning professional.

Demand Planning is one of the unique areas where the individual can either move up in Marketing, or Finance or into senior cadres in Supply Chain.

Why is this a very important career enhancing workshop to attend?

Demand Planning is a highly demanded skillset for a lucrative job in the supply chain industry in India or abroad.  This course is aimed at practitioners and newly aspiring professionals who want to enter the supply chain industry.

Attendees who complete the two day course and all individual and group exercises will be awarded a certificate of completion.  This will be the pre-cursor and required workshop to our certification program to be launched in 2012.

Get skills you can use at work

We will explain and demonstrate best practices in model selection, illustrate how to improve model quality, and teach you how to leverage the forecast measurement process.

Learn from industry experience

We will bring practical examples from our consulting experience.  We have consulted with clients in Consumer goods, Food and Beverage, Chemicals, Pharmaceuticals, Heavy Manufacturing, Aerospace, Medical Devices, Oil and Gas etc.

Network with peers

You will have the opportunity to meet, interact, and learn from other demand planning professionals with team challenges and networking exercises.  Attending this workshop will introduce you to our vast network of supply chain professionals and career opportunities in North America and Europe.   This is not a job offer, but this education is aimed at providing a skillset that is in short supply through out the world.

Add to your credentials

Upon completion, you will be awarded a certificate of completion from Demand Planning LLC, attesting to your newly-acquired skills in Demand Planning and Forecasting.  You will also get an opportunity to obtain additional resources to earn a certification in the future.  Program is in the works to be announced shortly.

Does the two day workshop in Bengaluru contains topics related to forecasting of rarely used spare parts or not?

Yes we talk about models to forecast and stock for rarely used spare parts otherwise known as intermittent demand.

While the focus is on forecasting and modeling, our approach is to marry up the business problem with the technology.

Look forward to seeing you in Bengaluru, Bahrain or Boston!!

Review the course at http://demandplanning.net/demandplanning_seminarIndia2.htm. 

We have collaborated with Knowerx India to take rupee payments if you can only register and pay in local currency.

Happy Forecasting!

Demand Planning.Net announces the Training workshops for 2012

November 14th, 2011 by Dr. Chockalingam

Demand Planning.Net is pleased to announce the following dates for the Demand Planning and Forecasting workshops in 2012.  If you are preparing your training budgets, you may want to plan for these workshops for your new hires as well as experienced professionals that are new to forecasting or just as a refresher for those who know the theory but need a hands-on perspective and experience in forecasting.

Demand Planning and Forecasting 2-Day Hands-on Workshop at three locations:

Bengaluru, India Jan 27-28, 2012 at the Chancery Pavilion, Bengaluru India. Learn more…
Bahrain, Mar 12-13, 2012 at the Crowne Plaza Hotel for Middle East clients Learn more…
Boston, MA May 23-24, 2012 at the Four Points by Sheraton Boston/Norwood. Learn more…

This will be followed by the Fall 2-day seminar in September 2012.  There is a possibility of a one day workshop on S&OP during the Summer in Burlington, VT.

We also are offering the one day modeling and metrics workshop that focuses on SAP APO DP.

SAP APO add on 3rd Day Workshop available in Bahrain on March 14, 2012 and Boston on May 25, 2012. Learn more…

Please review http://demandplanning.net/workshops.htm for details on all of the above training workshops.

 

Draper Team Aims to Improve Predictions Through SPADE 10/05/2011

November 7th, 2011 by Dr. Chockalingam

Press Release from Draper Laboratories

CAMBRIDGE, MA – Draper Laboratory is leading a team that aims to improve long-term intelligence predictions through software that weights most heavily forecasts from analysts who tend to be most accurate in particular fields like politics, world events, and economics.

The Intelligence Advanced Research Projects Activity (IARPA) is funding the effort through the Aggregative Contingent Estimation Program (ACE) with the hope of finding the most precise and timely way to crowd-source its predictions amongst its widely dispersed analysts.

Draper is leading a team named SP♠DE – the System for Prediction, Aggregation, Display, and Elicitation. The SP♠DE technical team is led by Dr. John Irvine, capability leader for information and decision support, and Dr. Sarah Miller, a senior cognitive science researcher. The team includes Drazen Prelec, a professor at the Sloan School of Management, as well as the Departments of Economics and Brain & Cognitive Sciences, at the Massachusetts Institute of Technology; Alexander Kirlik, professor and acting head of the human factors division at the University of Illinois; Dan Martin, director of MRAC, a psychology research and consulting firm; and Bill Welch, director of the Center for Intelligence Research Analysis & Training at Mercyhurst College in Erie, Penn.

While forecasts made a few days or weeks before an event are often accurate, the challenge is far greater to look long term in order to give policy makers the best opportunity for planning, said Stuart Peskoe, associate director for mission systems in Draper’s tactical systems group and SP♠DE project manager.

The SPADE team will be enhancing Prelec’s method of Bayesian analysis that scores most highly those analysts whose predictions exhibit a surprising level of mutual consistency. Miller and Kirlik have also studied how best to take advantage of the strengths of experts and algorithms while compensating for the weaknesses of both –and successfully tested their concept with fantasy baseball predictions and actual Major League Baseball results.

The team is looking for those with interest or expertise in economics, politics, culture, and global security to participate in the study via an interactive website at www.iSpade.net.

Draper Laboratory is a not-for-profit, engineering research and development organization dedicated to solving critical problems in national security, space systems, biomedical systems, and energy. Core capabilities include guidance, navigation and control; miniature low power systems; highly reliable complex systems; information and decision systems; autonomous systems; biomedical and chemical systems; and secure networks and communications.

For more information, contact www.ispade.net

Demand Planning in the Middle East – Training Workshop

November 4th, 2011 by Dr. Chockalingam

For the first time, we are bringing our hugely popular two day workshop on Demand Planning and Forecasting to the Middle East at the request of many Saudi and Emirates based Forecasters.  We have received many requests for this popular two-day course in Demand Planning and forecast Modeling.  We will also provide you with a forecasting software for a limited trial to explore the power of statistics in Forecasting.

March 12th (Mon) and 13th (Tues), 2012 – 2 Day Interactive Workshop in Manama, Bahrain at The Crowne Plaza

View and print seminar brochure (PDF)

Register Now! – Regular Price $995
Early-Bird pricing $895 until January 20, 2012

In this specialized two-day course, we will explain the modeling methodology and process behind accurate demand forecasts.

We will also illustrate how to effectively use promotional information to arrive at an event based 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.

If you are a new demand planner looking to enhance your knowledge of business forecasting, you cannot afford to miss this opportunity!

View more information at

http://demandplanning.net/demandplanning_tutorial_Bahrain.htm. 

I look forward to facilitating this workshop in March in Bahrain and to meeting many of the colleagues based in the Middle East and Europe.

There is also a one day workshop on Modeling and Metrics in SAP APO on Wednesday.   For SAP APO planners, it is ideal to take the three days as one combined workshop.

Please contact us if you have any questions.

 

Demand Planning and Forecasting in Bengaluru, India January 27-28, 2012

October 29th, 2011 by Dr. Chockalingam

After a two year hiatus, I am looking forward to facilitating our hugely popular two day workshop on Demand Planning and Forecasting in India on January 27 – 28, 2012 Friday and Saturday at the Chancery Pavilion in Bengaluru.  India is always exciting, different perspectives and different structures and even interesting demand profiles.

Yes, we have to deal with a fun challenge – explosive growth markets and ability of the forecasting models to recognize a variety of trend patterns and trend shifts.

This is a highly interactive hands on session that will introduce you to the key concepts in Demand Planning and Statistical Forecasting.  A popular forecasting software will be provided for class room use to illustrate the required forecasting models.  This will be a full license of a forecasting application that will run on Microsoft Excel.  This package can do Moving Average models, exponential smoothing models and ARIMA models along with other exotic models such as Dynamic Regressions, Croston’s Models and Bass Curves.  The attendees will have the opportunity to test drive their company data with this application to see how statistical modeling can be effectively leveraged to better forecast demand.
We will also have a session in forecasting using Excel.  Given Excel has been inseparable from the forecasting function, we will demonstrate a variety of methods that are available in Excel to construct simple yet useful forecasts.  These include Moving averages, double moving averages, First order exponential smoothing function built in Excel along with Regression models.

Based on some of the inputs from our clients, we will be doing a 45 minute session on how to forecast in excel using Decomposition models.  The Decomposition models can be used to forecast series that exhibit trend and seasonality without resorting to advanced modeling algorithms.

We will discuss Model Diagnostics, Forecasting by Decomposition, Exponential smoothing, Forecasting Metrics, and Exception Management.

You will get a variety of templates and calculation models in a CD along with relevant white papers and reading materials.  We are developing a certification program in the fourth quarter.  I am not sure if this will be ready in time for the India seminar.  But all participants may be presented with an opportunity to register for the certification to be taken online at a later date in the second quarter of 2012.  Let me know if you are interested in more details about the certification program.  Email me at info(at)demandplanning.net.

I look forward to meeting many of my linked-in India connections in person in January!

Dates: 27th and 28th January 2012

Where: the Chancery Pavilion, Bengaluru India

Visit here for agenda and other details:http://demandplanning.net/demandplanning_seminarIndia2.htm

SKU level forecasting or aggregate planning – the case for S&OP

October 6th, 2011 by Dr. Chockalingam

Talk to any supply planner, they will say they need a forecast at the SKU level.  The more detail the better.

So the demand planner is on the defensive, he needs to forecast at the most granular level to satisfy the demands of the supply chain.  Create and deliver a demand forecast at the SKU/location and sometimes at the SKU/customer/location level.  But the more detail you get, the more noisy the data gets and it becomes impossible to create good statistical models at that level.

It is important to have a software package  that allows you to get the forecast at that level.  However, analyzing, reviewing and consensing at that level has its perils.  Living too much at the detail level will definitely trap you from getting to the important challenges of the business and resolve true exceptions.

Looking at aggregate numbers for review and consensus among stakeholders leads to the Sales and Operations Planning process.  Truly balancing Supply and demand at the aggregate level will result in driving the stakeholders to understand the true business problems.

Is demand equal to what we can supply?

Can we answer this question at the product family or sub-family level first?  If not, can we smooth production so we build inventory to get ready for the peak demand?

If the answer is yes, then look at major MRP or schedule exceptions.  But these should be addressed internally in preparation to the S&OP meeting.  This is not a major S&OP decision.

Let us discuss more in a couple of weeks in Princeton, NJ.

http://www.demandplanning.net/demandplanning_tutorial_SIOP.htm.

Why moving averages in APO DP rarely move?

September 7th, 2011 by Dr. Chockalingam

When I was a beginning student of Statistics in High School, I was fascinated by moving averages.  This is pretty cool stuff to get an average that moves over time rather than the plain vanilla “sum it up and divide by the count” routines.

The question that we hear often from SAP APO users is about the “mysterious” behavior of the moving average model.  Many pronounce SAP APO Demand Planning module as weak the moment they see a constant straight line as the forecast after “trying very hard” with countless hours of model iterations!!

To some, APO DP often declares the constant as the “best” forecast.  And of course, the planners are frustrated.  Management is frustrated to see a constant forecast coming from a million-dollar package most of the time.

There are many factors that may be driving this frustrating challenge-

  1. The user settings may unnecessarily eliminate the information in the historical series leaving with not much but random variation.
  2. The configuration settings may have imposed constraints on the modeling options available to the users.  Although this was not deliberate on the part of the consultant who configured the system, the users are left with very basic models.

In a strange way, some consultants do not want to allow advanced modeling options, since they do not understand how these models behave themselves.  They do not want to be answering tough user questions on issues they are still researching!

If all the planner is left with are basic options like the Constant Model or the Moving Average Model, then they really have to settle for a straight line into the far horizon.

So let me answer the question why even moving averages become “dead” constant in the forecast horizon.

One of the important qualities of a forecast is robustness.  Robustness means the forecast does not change like a yo-yo just based on new historical data point.  So if you select a three period moving average, each new historical data point will change the forecast by one-third.

So the objective is not to mimic the history but to produce a forecast that minimizes the error. Theoretically, Moving averages should produce a constant forecast into the future at least after the first two periods.  The idea of the moving average is that it will change by at least one third of the impact of the new observation that is different from the
forecast.

Let us assume there is a series that looks like this:

917, 908, 902, 907, 908, 916, 903, 912, 916, 909………..

APO DP moving average model suggests a forecast of 910, 910, 910, 910……….. etc.

I would say that is a darn good forecast.  And this is not much different from another forecast that fancily varies between 905 and 915 every month.

Let us understand the difference in error in what is being proposed here.  A forecast that is 910 each month is off by less than 1% from another forecast that varies between 902 and 915 over the entire forecast horizon.

A contrived model that looks fancier with oscillations in results between 902 and 915 perhaps can be 1% better on average than another model that proposes to use a constant 910 every month. I don’t think the trade-off to improve forecast quality by 1% is worth the model search to come up with a more complex model that mimics
the history better.

The fact that you are choosing moving average means that the data series is relatively more stable. We as planners should let moving average do its job and move on to more complex items that need your attention – items that
have a persistent trend or seasonality or both.

Trying to fit a holt-winters model when the series begs you for a constant model is NOT a good use of time. Note that SAP APO classifies moving average under constant models.  In fact, specifying that you want Holt-Winters models in such a scenario will give you a First Order smoothing model which again gives you constant forecasts into the horizon.

Assuming you don’t have major mis-configuration issues, the demand planner is better off doing a product segmentation based on modelability and being discriminative about when to apply advanced models.

If you want to learn more about modeling in APO DP, you may be interested in our upcoming one-day workshop at http://www.demandplanning.net/modeling_metrics_in_apo.htm.

Predicta Forecasting Tool – New Kid on the block!!

August 18th, 2011 by Dr. Chockalingam

We had the opportunity to test drive the Predicta Forecasting application over the last couple of weeks.  This is an Excel add-in software available as off-the-shelf (or more appropriately off-the-net) package for forecast modeling and simulation of safety stock calculations.

Predicta gracioulsy offered us an Enterprise version for this evaluation and testing.

Right off the gate, the big advantage is it is an application that easily plugs into your Excel 2010 (the company says it is compatible with Excel 2007 and up).

The look and feel is great.  The charts are very pretty and it provides a variety of statistics if you are an intensive modeler trying to develop models all day.  What we found interesting was the software also provided Theil’s U-statistic in addition to the commonly reported error metrics such as MPE, MAPE, RMSE and R-squared.

The engine behind the tool provides popular statistical modeling options such as exponential smoothing, double exponential smoothing, Holt-Winters methods, and Regression methods.   The reporting for analysis is pretty detailed and the graphs are Excel graphs so adjustments is easy – we just did not find an easy way to unhide the tab to manipulate the underlying data that is used in the graph.

The Predicta data-application-model is driven by Excel as your main spreadsheet while Predicta is an Excel Add-on that sits with buttons available for what you want to do as an additional menu item.  You can see all the models and the functional options all available as buttons:

  • Exponential Smoothing (Modeling)
  • Holt-Winters (Modeling)
  • One-Click (creates a forecast on one-click)
  • Best-fit (picks the best model among a list of options)
  • Safety stock calculations (function)

Contrast this with Forecastpro, another popular Excel package available in the market.  Their data-application-model is where Excel just acts as a data provider while you work completely in the software.  You change models, change parameters and test different things out and you only go back to excel if you want to reload the data and load back the results.

So there are pros and cons with these approaches.  While you work completely in Excel in Predicta, this can also be tedious to do modeling since it creates sheets and sheets of excel output each time you change a model or a minor parameter adjustment.

Predicta says the Enterprise version can do modeling of unlimited number of SKUs.  However, we could not load more than one SKU while using the best fit method and not more than three SKUs while using the Holt-Winters method.

The one click is the only option that allows you to model multiple SKUs at the same time.  However, the challenge here is you have to select a particular method ahead of time.  The software does not pick the best fit of all available models.  So for batch forecasting, you will be forced to use the one-click method but this depends on the planner’s prior knowledge of the data and demand profile.

In our forecast comparisons, the software did not yield the most efficient Holt Winters forecasts.  While researching this, the Product manager admitted that the parameter search is using a grid that is only .10 apart.  The company promised that they will be improving this shortly so more granular parameters can be estimated so this will improve the efficiency of the estimates.

The strangest thing was – the forecast horizon was limited to just one period when picking the simpler models – exponential smoothing, Moving Average etc.  Although we know that the forecast will be a constant, this is an inconvenience for the planner not to get the forecasts copied over for the horizon they want.

Given this is the first release of the software, more improvements are imperative to make this competitive with other tools in the space.  The biggest challenge I see is the data management – where the software produces tons of data for every little model test intead of over-writing existing outputs.

We also noticed that there is no methodology to address SKUs with intermittent demand.

Our recommendations:

  1. I think it will be better to think of the average customer as a planner that is looking for results rather than a rocket scientist who will like to admire the beauty of the models and the charts all day.
  2. Provide an user option to either over-write or keep existing results when running another iteration of the model.
  3. Provide a best fit or an expert engine option that suggests only one forecast and results instead of throwing off multiple models and identifying the best fit.  Forecasters are looking for a good forecast along with statistics that substantiate the best fit.
  4. The one-click model should be intelligent enough to provide the best fit in each case instead of requesting the planner to pick one model option for all the SKUs that are modeled in one-click.  This is makes the one click unusable.
  5. Allow multiple skus to be picked when using the best fit or the single model.  I understand this may cause performance issues but that is a challenge that needs to be addressed.

A nice thing about Predicta is it gives a clean calculation of safety stock, re-order point and Min-Max in one shot.  Although these are not optimized for dynamic lot sizes and variable lead times, this is a good start and gives a good feel for the impact of variability on your inventory parameters.  The safety stock is calculated using the standard deviation of demand (instead of in-sample forecast error) and the lead time demand is just the forecasted demand from the model that is selected.

We would like to thank Predicta for making the software available to us to do this testing.  I hope the company can improve the software substantially before the next release.

You can find more info on the software and purchase a copy at http://predictasolutions.com/.

S&OP Best practice: Engage in ongoing cross-functional communication rather than wait for “the meeting” once a month!

August 5th, 2011 by Dr. Chockalingam

S&OP Best practice:  Engage in ongoing cross-functional communication rather than wait for “the meeting” once a month!

Many organizations have respective functional departments for finance, supply management, demand management and production planning. But some organizations are plagued by the lack of structured interdepartmental communication which affects their operational efficiency.  This leads to disparities between financial forecast and operational forecast.

To resolve this complex situation it is recommended to increase the interdepartmental communication – you can resolve this by thinking of the S & OP as a process rather than a collection of meetings that happens at periodic intervals. You can also see readers discuss this topic on our Linked In group.

In our upcoming 2 day tutorial workshop on Sales and Operations Planning (http://demandplanning.net/demandplanning_tutorial_SIOP.htm ), we will be talking about the S & OP process and why inter-departmental communication is very important to make the S & OP process successful. We will also talk about what form of communication this should be – communication that uses the common language, numbers people can understand and are interested in.

This is your chance to discuss your pain points and current practices. At the end of each session we will analyze what which best practice you can take away from that session.

In this workshop we will show you our five step approach for mapping and implementing S & OP process.

You can register for this and the other workshops on Demand Planning, and SAP APO DP Modeling at  http://demandplanning.net/seminar_anregistrations.php