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About Demand Planning LLC

Demand Planning LLC, based in Boston MA, is a consulting boutique comprised of seasoned experts with real-world supply chain experience and subject-matter expertise in demand forecasting, S&OP, Customer planning, and supply chain strategy.

We provide process and solutions consulting, as well as customized training across a variety of industries.

Through our knowledge portal DemandPlanning.Net, we offer a full menu of training programs through in-person and online courses, as well as a variety of informational articles, downloadable calculation templates, and a unique Demand Planning discussion forum.

  • 01Jan

    As we are about to ring in the New Year, here is a moment to contemplate on what we have seen in 2012 and what looks like in 2013.

    It appears 2013 will be the year to shift major paradigms!

    Since I am not psychic, I am just looking at trends to see if they extend, fold or just just go no where!!

    1. The Big Data Bandwagon will get even bigger!

    Just like outsourcing was the buzzword in 2002, Big data is the current buzzword to attract venture funds, IT investments and even for job seekers to find a higher-paying job! Big Data buzz will get even bigger in 2013!

    2. Integrated Business Planning will take over from S&OP!

    More c-Level managers will start to look for a process that can effectively leverage Big Data above to make decisions based on predictive analytics! Only the thought leadership will happen in 2013. The technology and the software field is wide open with no identifiable players ready to facilitate IBP.

    3. Outsourcing Demand Planning Best practices will become more prevalent

    Companies in SMB will look to outsource their demand planning efforts, not necessarily eliminate demand planners, but the process to achieve consistency and sustainability in demand planning!

    4. We will see much higher visibility of Demand Management!

    The entire process to demand shape, sense, plan and manage demand will achieve higher visibility in Corporate America. People with such skills along with business experience will be most sought after for lucrative positions through out the world!

    5. User-unfriendly technologies will suffer a bigger blow in 2013!

    Software technologies that are not user-centric or user-focused will find themselves losing market share in 2013 with potential casualties including SAP and Apple (yes – Apple Computer has joined that camp in the post-Jobs era)!

    Let us prepare for 2013 and do the right thing and make the right moves!

    All of us at Demand Planning Net wish you a happy and prosperous New Year 2013! Enjoy a fun and safe New Year’s Eve!

    Sincerely,
    Mark Chockalingam
    Demand Planning LLC

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  • 23Nov

    This has been a recurring challenge and a potential land mine when it comes to the raw number crunching in demand planning.  Zeroes and Nulls……….

    Is the Null the same as a zero?

    Although excel formatting can code a zero as a dash, can a zero be interpreted as a Null?  If so when and when not?

    Similarly, including some may also be bad for the health of your demand forecast.

    Leading zeroes – Will you include them in developing a statistically modeled forecast.

    How about nulls in the middle of the data? These either show up as nulls, .dots, or some times as zeroes.

    Ok.  Now that I have asked too many questions, I will also propose some answers for you.

    Generally Nulls can never be treated as zeroes.  They are different things.  Nulls mean nothing, the absence of anything.  Nulls mean no data or no observation.  If you average a series with nulls, the nulls count in either the numerator or the denominator.  Zeroes are different.  If you average them, they will have no contribution to the numerator but will count as an observation in the denominator so you will have your average reduced with the presence of zeroes.

    At least in demand forecasting, we can coin the following rules:

    1.  Leading Zeroes can be interpreted as Nulls. 

    At times a product may be slated to launch in a specific month and hence the system may start recording zeroes as data if the launch is delayed.  Leaving them in may result in a poor statistical forecast.

    2.  Nulls in the middle can be interpreted as zeroes.

    Some systems may record nulls if there is no demand activity.  However if the nulls occur in the middle of a time series history, I would recommend they be treated as zeroes.   Most intermittent demand data is characterized by zero sales volume frequently.  If you leave them as nulls, this will inflate your average and generally result in a upwardly biased demand forecast.

    Imagine this scenario:

    90 Null Null 90 Null 90 Null Null 90 Null Null Null 90.

    If you ignore the null, then your demand forecast will be 90 per month if you use the average as the model to forecast. If you interpret the null to be zero, then your average will be 30 units a month.  If the customer has a three month requirement of 90 units and orders only once in every three months, then 30 per unit seems more likely as a forecast.

    3.  Trailing zeroes and Nulls

    Exclude or include?  What do you do with these?

    They look harmless to me if you have a decent exponential smoothing engine. Do you agree?

    We will discuss our approach in detail in our Demand Planning and Sales Forecasting Tutorial workshops scheduled for Feb 2013 in Dallas, TX.  We go into the nuts and bolts of many practical challenges that demand planners face.  This is why our workshop is considered to be the most practical and hands-on when it comes to Training for Demand Forecasters.

    Ignoring these nulls and zeroes can be perilous and lead you down the wrong path.  This may affect both your forecasting and inventory setting.  More dangerous to ignore these if you are calculating safety stock parameters.

    You can see more info on our workshop at http://demandplanning.net/demandplanning_tutorialCA.htm. I am told that we have just a handful of seats left for the early bird quota.

    Have a great holiday!

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  • 14Jun

    In the post jobs-era, Apple has even grown bigger in terms of the accolades and the lime light it is enjoying.

    • iPhone 4S launching SIRI your voice slave.
    • iPad3, just launched after I bought my iPad2.
    • Tim Cook becoming the new jobs-like cZar of Apple company.  Supply Chain Pundits should take pride in the fact that he started as a humble supply chain manager in Apple.

    I only remember reading it in my MBA courses how Apple became prey to the open architecture of the WINTEL computers.  Microsoft supplied the OS, Intel made the engines and anyone can put together an IBM clone computer.  It so ended up that everyone other than IBM started making the PCs – remember IBM sold the PC business in its entirety to Lenovo.  Apple Stock went to the single digits in the mid-eighties.  Barely survived until the return of Jobs and the launch of the iMac and the iPod.

    Then it flourished.  Jobs magic created a variety of iProducts – iPod, iPhone, iPad and iWhat………….  The company is the most valued in the world at $535 Billion dollars as of June 2012.

    The valuation represents the sum of all expected future profits or what the investors are perceiving it can make in profits in the future.  Another way to say it is the company has boat loads of iMagic up its sleeves to make more money not just from the iProducts it already has but also the new iPotential it has in its pipeline and to be released.

    Just in terms of size comparison, the following statements reveal how valuable the company is:

    1.  It has $28 Billion dollars in Cash

    2.  The second largest company Exxon Mobil is $200 Billion smaller in market cap.

    3.  The Value of the company at more than half a trillion dollars is one-thirtieth the GDP of the United States.

    4.  The company’s Market cap exceeds the Gross Domestic products of most countries and just as large as the economy of Saudi Arabia or Sweden.

    Now it strangely feels like Deja Vu again.  However, WINTEL is not back to unseat Apple.  Perhaps something similar.

    There is a company called Google that has an OS called Android.  It makes it available to any handset maker that wants to use it.  HTC, Samsung and LG are happy to make those phones and sell it on the cheap.  And Google has decided to buy its own handset maker in the form of Motorola, so it has a captive unit that also turns out DROID phones.  Sleek, futuristic, and just smoothly and rapidly evolving.

    And Apple is starting to make mistakes……….  mostly in the OS.  Every upgrade I installed on my iPhone 4 since the passing of dear Steve Jobs has been a fiasco.  I lost my music, data and apps and other pesky issues.  Losing the music is the strangest thing.  The music all disappeared from the iPhone but the computer said it is still there……… Oh Well.  Had to wipe and reload everything.  Not fun!  Apple may say I am techy enough for the new OS.  But Jobs never made products for geeks or tech people.  He made usable products for the users. period.

    When another OS looks like the greatest threat for Apple, the company is bungling on its OS.

    I know Apple always looked to Microsoft to make office applications for its iMacs.

    Is there a day to come when Apple may potentially become a handset maker licensing the Android OS?

    Quo vadis Apple?

  • 23Mar

    Companies are rushing to upgrade from the APO 4.1 and 5.0 versions to the new SAP SCM 7.0  As the purse strings are loosening up this year, companies are spending more money in ECC and application upgrades.

    What are the big differences between the 4.0/5.0 vs. 7.0?  There are some marginal improvements that the tech shop may admire but anything for the planning community?!

    We also hear that the planners have not been using the Statistical modeling features in APO.  Will upgrading to 7.0 persuade the planners to use the Stat Models more?  Not just more, just even barely?

    IT implementation teams say that Stat models are not a priority given the budget constraints they have.  So more millions before and no stat models.  Now five years and many millions later, we have a shiny new upgrade and again the stat models are not a priority.

    I have been preaching Usability for the past few years.

    Put together fine tools  – But help the users in making the transition to the tool – give them better understanding – Make the new tool more usable!

    Give them the reports they need.  Provide them an exception based workflow!

    APO has good statistical models.  They will help you move the peanut forward but only if these models are better understood and leveraged.

    We just re-launched the marketing campaign for our Usability Consulting – Model tuning and model matching to product profiles are important elements of the Usability training. 

    Once implemented the Usability project will harmonize the use of models across planners from various geographies for the same business/product family.  There will be streamlined work flow.

    We help you answer the following questions:

    1. Am I using a Pareto Approach in my APO planning process?
    2. How can I leverage APO DP to improve our forecast accuracy?
    3. Why does APO mostly give me flat forecasts? How do I fix this?
    4. What are Alpha, Beta, Gamma, Sigma and Theta? How do I leverage these parameters?
    5. What is the correct level to model so as to improve the overall accuracy at the SKU level?
    6. What are weighting profiles? How does it affect my final forecast?
    7. How can I control time trend using trend dampening profiles?
    8. Are there products and customers that are better left to APO’s automated modeling strategy?
    9. Which models to choose for what family of SKUs?
    10. What are custom modeling profiles?
    11. How is APO helping us simplify and improve the promotional planning process?
    12. How do I create Multiple Linear Regression Models in APO?
    13. Are we using the system defined error metrics in APO? Why are they different from the classic MAPE calculations?
    14. How do you conduct phase-in/phase-out of products?
    15. When should I not use the Croston’s Model?
    16. Why am I getting 9,000+ alerts every morning?

    Perhaps the stress test of your new implementation or upgrade will be to ask the team if they can answer the above questions.

    Our Model tuning and training project can be launched any time -but it is better to launch it sometime during the middle of the configuration calendar before the go-live.  This way the training to the planners can be combined with the Navigation training.

    The benefits will be substantial:  improved forecasting process, workflow and significant supply chain benefits and cost savings.

    What does it cost you?  Not much – perhaps one-fiftieth of what you paid for the APO DP implementation or some where in that ball park.  We finish everything in ten to twelve calendar weeks.

    The detailed brochure on this Model Tuning and Training service is available for download at http://demandplanning.net/documents/SAP-APO-DP_ModelTuning_v2.pdf.

    Happy Forecasting!

    Mark Chockalingam

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  • 10Jul

    A user in an APO forum lamented:

    “I am trying to use the Moving Average option in APO DP but I get a static forecast that remains constant for all the future months based on the history.  I would like the statistical forecast to be a moving target not a constant.  Not sure how to achieve this?!

    “All I get is the same statistical forecast volume for all 24 months. This is not want we are looking for.  The system is giving me a forecast like this:  month1 – 915, month2 – 915,… month 24 – 915

    “But I want the system to give me forecast that is different each month: 
    Future: month1 – 915, month2 – 902,… month 24 – 908.”

    Before we go too far with the micro details of these numbers, let us first realize some qualities of a good statistical forecast. 

    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 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.

    Other than this, let us understand the difference in error in what is being proposed here.  A forecast that is 915 each month is off by 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 915 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. 

    If you want to learn more about error metrics, you may be interested in http://www.demandplanning.net/apoMetrics_webworkshops.htm.

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