Category Archives: Execution-Level Forecasting

Do You Know Your Execution Level for Your Demand Forecasting?

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I think this blog falls under the category – someone is always thinking, it just might not always be you.

You have hopefully read on this blog or perhaps in other venues the idea that demand forecasting has its greatest supply chain impact (and therefore financial impact) when improved at the execution level –the level that helps maximize the operational and financial performance.

And typically the implication and in some cases the outright declaration is that the lower the level of detail the better – supply chains do not produce product families or product categories.  They make actual products, SKUs, and items.  Forecasting at the family or category level only results in more error at the product level.  So it makes sense to ensure that the SKU level forecasting is where you measurably improve forecasting accuracy.

But … if SKU is good, SKU by location is better. And if SKU by location is better, SKU by Ship-to customer location by location is even better.  This could go on for awhile but the point is, the overall push has been for more information and accuracy at lower and lower levels of detail.

However, we recently ran into a company where that was not the case.  It is a consumer products company that operates at a very high level of RPMs.  And for their product and for their supply chain, forecasting at the SKU or lower level really does not make sense.  What makes the most sense for them is forecasting by product category or what they would refer to as chassis.  If they can get demand for the chassis accurately forecasted (said chassis representing 90% to 95% of the total material cost), then turning a chassis into a finished SKU is a quick and efficient process. The actual plates and other finishing components are inexpensive, easy and cost effective to order in bulk, quick to assemble, and are interchangeable with most of the chassis.

What’s the point?  It comes down to the fact that when you start the process of improving your forecast (for all the reasons that have been outlined many times), a real fundamental key to success is stepping back and thinking through what is your company’s execution level of operation?  Thinking through the execution level appropriate for you includes not just your supply chain but your entire value chain, especially as data proliferates through increased collaboration among enterprises.  Getting the answer right is critical to driving improved customer service, cash flow, and profitability.

Forecasting Software to Increase Your ROI | Demand Foresight

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Happy New Year!  2013 looks to bring a whole host of new challenges and opportunities for businesses to differentiate themselves and to thrive in an increasingly more competitive marketplace – just like last year.  Brings to mind the old quote from Jean-Baptiste Alphonse Karr (although probably more familiar to people who are fans of Kenny Chesney or Jon Bon Jovi) – the more things change, the more they stay the same.

Using that quote as an incredibly clever transition device, whatever the challenges and opportunities before us, there are a few key basic truths and one of the them is that as business people we have a fiduciary responsibility to maximize the value of our businesses over time and that is often measured through increasing cash flow and pre-tax profitability (net profitability has become a much more complex conversation).

Therefore, to start the year, I thought we would revisit and refine the value proposition of dramatically reducing your forecasting error.  All of the research supports that in today’s operating environment, improved forecasting is the number one option available, from an operational S&OP point of view, to most effectively, measurably and quickly improve your value chain performance and therefore improve cash flow, return on capital and pre-tax profitability.

How specifically can improved forecasting improve value chain performance? Not necessarily in order of importance or impact, improved forecasting should allow you to

  1. Increase revenues because:
    • Sales focus on their most profitable customers and products
    • Marketing more effectively supports sales and brand strategies
    • Customer service increases because there are less out-of-stocks
  2. Improve utilization of working capital because:
    • Inventories are reduced closer to what is needed
    • Raw materials, components and finished goods are purchased more in line with optimized production or deployment plans
    • Order to cash cycle times are greatly reduced
  3. Improve Return on Capital Employed because greater accuracy allows for more effective:
    • Master Scheduling of plant and materials (and personnel but often this is not included in capital calculation)
    • Constrained Planning
    • New asset / capital investment

These represent what can be improved – no doubt you are asking to what degree can I improve my returns on investment and capital employed and cash flow and pre-tax profitability.

Results are obviously dependent on the exact situation within each company however as a general rule of thumb, our experience shows that a 25% reduction in forecast error translates into a minimum 5% improvement in pre-tax profitability.

However, perhaps more compelling, independent research shows equal or greater impacts.

Specifically,

Dr. Hau Lee is the Thoma Professor of Operations, Information, and Technology at Stanford University; Co-director of The Stanford Global Supply Chain Management Forum; Director of Managing Your Supply Chain for Global Competitiveness Executive Program.

Given Dr. Lee’s long term research and cooperation with client companies, the impact of improving forecasting and focusing on demand drivers is significant.

“Distorted information from one end of a supply chain to the other can lead to tremendous inefficiencies: excessive inventory investment, poor customer service, lost revenues, misguided capacity plans, inactive transportation, and missed production schedules.”

 “I have already seen some companies using new software tools to manage their businesses based on demand, with results ranging between 50% and 100% in net profit increases, which in turn can easily be translated into enormous increases in shareholder and market values.”

Dr. John T. (Tom) Mentzer was the Harry J. and Vivienne R. Bruce Chair of Excellence in Business in the Department of Marketing, Logistics and Transportation at the University of Tennessee. He was a prolific researcher and author with 5 books on value chain excellence and competitive differentiation not to mention hundreds of articles to his name.

Dr. Mentzer extended his research, through the help of many colleagues and collaborators, to the measurable on a company’s performance. The single most clarifying result of improved forecasting highlight by Dr. Mentzer:

An increase of shareholder value of 15% or more!

Lastly, we refer to the Gartner Group which includes the recently merged business/supply chain analysts from AMR Research. There are a host of strong practitioners such as Noha Tohamy, Tim Payne, Mike Griswold, Dennis Gaughin, and Steve Steuterman just to name a few. Since January 2011 they have published a large number of research papers and articles that highlight the impact of improved demand forecasting. Their cumulative research has pointed to some significant findings.

Gartner’s measurable impacts of improved forecasting and demand planning:

  • 1% to 3% revenue increases
  • 15% to 30% inventory reductions
  • 20% to 30% order fill rate increases (Demand Foresight note – important to do 2 and 3 simultaneously)
  • 10% to 15% decreases in obsolete inventory
  • 3% to 5% increases in gross margin

Do you have an aggressive revenue, margin, cash flow and profitability plan for 2013 and/or for a number of years ahead? Are you mixing it up with aggressive and creative competition? Trying to differentiate your company and yourself?

I hope that as we kick off 2013 and all the possibilities and potentials still lie in front of us, you will take to heart that one of the most powerful investments you can make (and should make given fiduciary responsibility) that will have an immediate and long term positive impact on your performance (intentionally left blank – your company? Yours?)  is the investment in dramatically improving forecasting accuracy.

Looking forward to the conversations that are coming up.

 

Demand Forecasting – Proven bang for the buck on the bottom line

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Solving business problems and helping our partners create future profits – Demand Foresight is completely focused on these goals. We focus on delivering upon these through improving demand planning and overall S&OP operations and helping support transition to being a demand driven company.  Our experience in this work helps us quantify the impact of what we do – a minimum 5% improvement in pre-tax profitability.  But obviously we are not the only game in town and there is a tremendous body of work around demand forecasting and the impact of improving the forecast on various components of the supply/value chain.  It was brought up that we had never really highlighted some of this research so we went back and took a look at some of the source inspiration for our focus.  I hope you find this of value.

First up is Dr. Hau Lee.  He is the Thoma Professor of Operations, Information, and Technology at Stanford University; Co director of The Stanford Global Supply Chain Management Forum;  Director of Managing Your Supply Chain for Global Competitiveness Executive Program.

Dr. Lee’s signature idea is the “bullwhip effect,” a concept he co-developed in the 1990s, which has become a basic tenet in both academia and industry. When a person cracks a bullwhip, the small movements at the wrist produce huge waves at the other end of the whip, which describes how information on demand becomes increasingly exaggerated and distorted as it moves up the supply chain from customer to manufacturer to supplier, driving up costs and hurting efficiency.

There are several components to the cause, effect, and solution to the bullwhip effect which you can start to explore through the attached links but one key is that the demand forecasting capability plays a large role in the bullwhip and the effects can be devastating to a company’s value chain.  Specifically:

“Distorted information from one end of a supply chain to the other can lead to tremendous inefficiencies: excessive inventory investment, poor customer service, lost revenues, misguided capacity plans, inactive transportation, and missed production schedules.”

Given Dr. Lee’s long term research and cooperation with client companies, the impact of improving forecasting and focusing on demand drivers is significant.

“I have already seen some companies using new software tools to manage their businesses based on demand, with results ranging between 50% and 100% in net profit increases, which in turn can easily be translated into enormous increases in shareholder and market values.”

http://www.gsb.stanford.edu/news/bmag/sbsm1008/feature-lee.html

Next up is Dr. John Mentzer.  Dr. John T. (Tom) Mentzer was the Harry J. and Vivienne R. Bruce Chair of Excellence in Business in the Department of Marketing, Logistics and Transportation at the University of Tennessee. He was a prolific researcher and author with 5 books on value chain excellence and competitive differentiation not to mention hundreds of articles to his name.

One of his key areas of research highlighted competitive differentiation and included was a fairly definitive summary of what it took to develop a competitive differentiation in demand forecasting and demand planning.

Specifically, here are Dr. Mentzers’ 7 Keys to better forecasting:

  1. Understand what forecasting is and is not

  2. Forecast demand, plan supply

  3. Communication, cooperation, and collaboration

  4. Eliminate islands of analysis

  5. Use tools wisely

  6. Make it Important

  7. Measure, measure, measure

Most important of all was that Dr. Mentzer extended his research, through the help of many colleagues and collaborators, to the measurable impact (following his own guidance – measure) on a company’s performance.  There are a number of components to the result most of which you can begin to explore through the included links but from the point of view of an executive and/or member of the vaunted c-suite with specific fiduciary responsibility to all stakeholders of a company – the single most clarifying result of improved forecasting highlight by Dr.  Mentzer:

An increase of shareholder value of 15% or more!

http://bus.utk.edu/supplychain/forecasting/docs/Impact%20of%20Forecasting%20F99.pdf

http://www.uam.es/personal_pdi/economicas/rmc/prevision/pdf/seven_keys.pdf

Lastly, we referred to our friends at Garter which includes the recently merged business/supply chain analysts from AMR Research.  There are a host of strong practitioners such as Noha Tohamy, Tim Payne, Mike Griswold, Dennis Gaughin, and Steve Steurterman just to name a few. Since January 2011 they have published a large number of research papers and articles that highlight the impact of improved demand forecasting.  Unfortunately here we cannot include the source documentation links as that goes against policy and legal agreements, but please feel free to contact Gartner directly (www.gartner.com).  As they are a potentially important source of information for companies looking to make strategic investments in demand forecasting, sales and operations planning, and demand driven supply chains and networks.

Relevant to this blog post, their cumulative research has pointed to some significant findings.

Gartner’s measurable impacts of improved forecasting and demand planning:

  1. 1% to 3% revenue increases

  2. 15% to 30% inventory reductions

  3. 20% to 30% order fill rate increases (Demand Foresight note – important to do 2 and 3 simultaneously)

  4. 10% to 15% decreases in obsolete inventory

  5. 3% to 5% increases in gross margin

Independent of Demand Foresight and its experiences working with it partners, there is great research ongoing that undeniably highlights the benefits of focusing on improving demand forecasting and demand planning.  However, one consistent anomaly (kind of an oxymoron – A consistent anomaly?) that we notice is that while this highlighted research above as well as others all emphasize the importance of demand forecasting and measure the benefits of improved demand planning, very few of them talk about specific impacts based on higher percentages of accuracy.  Our suggestion and potential contribution to the field is what is the impact of improving accuracy by 5%? 10%?

Or as we ask all of our partners and potential partners – what would a minimum 25% reduction in forecast error mean to your bottom line?  Judging from our experience and the research– a huge amount!

 

Compete To Be Unique

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Focus on Innovating to Create Superior Value For Chosen Customers  

- Joan Magretta, Stop Competing to Be the Best, Harvard Business Review, 30 Nov 2011

You know the phrase “marching to the beat of a different drummer” is a way of saying someone isn’t following the status quo and is standing out from the crowd. It’s generally not a positive statement. We disagree wholeheartedly. Continue reading →

In response to: “How Manufacturing Software Should Adapt to Support Lean Principles”

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In response to: “How Manufacturing Software Should Adapt to Support Lean Principles”

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ERP Analyst, Software Advice
December 16, 2011

http://blog.softwareadvice.com/articles/manufacturing/how-manufacturing-software-should-adapt-to-support-lean-principles-1121511/.
Nice position article; we appreciate thoughtful discussion on issues critical to optimizing value chain effectiveness and profitability. I think productivity is even critical today given current competitive and regulatory environments.  That said, I am not sure I agree entirely with your point of view: I think you miss the other side of the equation which, together with your position, would actually create the cohesion you espouse.

So a couple of two or three points to consider.

First, one consistent between the two philosophies is the need for production requirements i.e. demand; it goes without arguing that the more accurate the production requirements, the better both will perform. So one way to bridge the gap between the two is to agree that both approaches are made better through improved demand planning and specifically improved forecast accuracy at the execution level.  It does no good to plan production, in either approach, to 4 decimal places only to have the forecast or production requirement end up being off by 30 or 40 or 50% at the execution level.  I am sure this point does not surprise you coming from me.

Second, this is an important discussion because it focuses on execution which is important to us.  No matter how accurate a forecast, it is worthless unless used to improve specific supply chain activities within the flow that you rightly highlight in your discussion.

Lastly, the core hypothesis is that software can and should work to accommodate “lean” and you highlight three areas within which to do so.  And, coming from the perspective of lean, these are solid focus points that I would agree should be address; I would go so far as to say they are being addressed by certain S&OP and manufacturing software vendors.

However, I would argue that lean also needs to grow and adjust to accommodate the principles of MRP.  There are some who argue that lean was developed in the vacuum of driving an accurate forecast and demand plan – hence the revival of demand driven supply chains by the people you mentioned as well as Gartner/AMR and others.  in general is a reactive dynamic; given a specific production requirement, what do we need to make and then how do we do so most efficiently.  And in a perfect world that is great.  However, what if the needed production requirements change?  What if they change by 40% (up or down) in a 2 week window?  What if the vendor does not show up with the needed WIP until 7 days later?  Not everything goes perfectly and this is where MRP and it related and perhaps even more important cousin DRP come into play.

When done well, DRP/MRP take into account variables such as forecast error, vendor performance, inventory costs (full costs), order fill rates and consumption patterns (to name a few) in order to help anticipate issues and drive supply chain operating decisions not only in optimizing performance for today but also for various time frames into the future based on lead times and customer promises etc. and in so doing, help minimize the risks of disruption.  Practically, this helps drive decisions such as what specific inventory to carry and who much which would actually work to make lean perform that much better in a more flexible manger.

There is no question that software can always look to improve ease of use, flexibility and value add.  But it should do so within a framework that takes advantage of what technology can do while supporting operational philosophies such as lean so that both sides can progress.  This is true for expansive ERP systems as well as useful spreadsheets.  And, if they are expected to execute based on a forecast with measurably decreasing forecast error, there is no need for these two approaches to be mutually exclusive.