The first point they make is that for most companies, Excel is not a viable S&OP tool.

• Anyone who has done extensive work in Excel knows that it is a very powerful tool that works best with smaller data sets.  Companies managing a complex supply chain soon find that they are stretching Excel’s boundaries to the breaking point.
• Modern S&OP process have a significant “what-if” component to them.  While it is easy to make high level changes to Excel, understanding what the real impact of these changes are, is simply not possible.  Consider a typical S&OP decision…what-if we were to add a promotion for this product line? A simple question, but a complex answer.  Sure, you can change the forecast quantities in Excel, and that can show change to revenue.  But what-if the product line is constrained?  What is the purchasing spend going to be to support this?  A simple Excel model simply cannot support this level of granularity.
• Excel doesn’t support alerts or lend itself to managing by exception.  Once your S&OP plan is set, you need to monitor performance against it.  Sure, you can see how you’ve performed at the next S&OP meeting, but isn’t that too late?

I’ve gone into some details about how Excel is not the right tool for S&OP (and other things) in other posts, if you are interested, you can find them here;

Is Excel the right tool for S&OP
How are spreadsheets like cockroaches
The endless debate: Is S&OP about technology
When spreadsheets go bad

So, if Excel is not the right tool for S&OP, what is?  Rather than call out a specific tool, let’s look at some criteria that you need to consider when looking for an S&OP application:

• I mentioned that Excel is not a good tool for S&OP is because it doesn’t support “what-if” analysis.  This is obviously something you need to look for in any tool for long range planning.  But simply allowing you to hive off a version of the plan and make a change is not enough.  The “what-if” analysis must provide detailed analysis as to what the impact of a given change will be throughout the supply chain.  A key supplier of low level components was just hit by a flood and won’t be shipping parts for six months – what impact will this have on my production?  What-if demand increases on one of my product lines?  What impact does this have on a constrained resource?… on my contract manufacturers?… on my suppliers?  Only a system with full supply chain analytics can address these questions.

• A related requirement is integration.  If you are going to provide answers to the “what-if” questions above, you will likely need to have detailed information from multiple manufacturing centers around the world. These centers in all likelihood are running a variety of disparate ERP systems, so your tool will need to integrate across all these systems and bring the data in to a single environment.

• As mentioned earlier, the ability to monitor performance against the plan and report on exceptions is key.  A S&OP plan is good.  A S&OP plan that you monitor and react to when underperforming is truly powerful.

There are several other factors that can play into your selection of a system for S&OP, but I think these are key ones.   What tools are you using for S&OP planning?  Are you evaluating new tools?  What factors are you considering?  Comment back and let us know!

Aamer Rehman, vice president, manufacturing solutions here at Kinaxis, serves as the conference chairperson for Day 1 of the event, on January 26. As the chairperson, he will introduce each speaker, lead the Q&A after each session, and share his personal experiences and key highlights of the topics discussed. Aamer will also present the session “Continuous Sales & Operations Planning for the Manufacturing Sector” on Friday, January 27, at 11:30 am.

Here is the session abstract:

Planning has long been segmented into different isolated activities that reflect organizational structures and functional goals, leading to long, ineffective, and inefficient planning cycles. For maximized value, sales and operations planning (S&OP) must be a truly cross-functional activity that can directly and simultaneously address both individual departmental goals and joint corporate objectives. In this session, you will learn about the specific technology and process requirements to achieve a continuous and collaborative S&OP capability as it applies to the manufacturing industry in particular.

A recording of this session and slide deck will be made available shortly after the event. Stay tuned!

If you’re at the show, stop by booth #7 and say hi to the Kinaxis team! Also, make sure to follow the hashtag #SOPLVS on Twitter to get real-time updates from the event.

For more information on the Sales & Operations Planning Innovation Summit, visit: http://operations.theiegroup.com/sop-lasvegas

An early practitioner who became famous in our field, Ollie Wight, described a good, realistic schedule as basic and fundamental to the health and integrity of a good MRP planning process.  He also described the aftermath result of poor unrealistic scheduling as the informal systems of hotlists and shortage meetings engulfing the formal planning process.  The MRP planning process still exists, today, in its original form, as the foundation of our evolved MRP, Closed Loop MRP, MRPII and ERP systems.

Back in 1973, I was a young college graduate living in Columbus, Ohio.  I was very fortunate in my first job as a Materiel Controller (Buyer/Planner) to work with the first computerized MRP software package developed by IBM and APICS, the IBM PICS (Production and Inventory Control System) Package.  During those two years I learned a lot about the computerized MRP planning process and wondered how this complicated and detailed process was ever achieved prior to the invention of the computer.

IBM in cooperation with APICS modeled this software package from the most efficient manual planning processes of manufacturing companies such as Steelcase and Black and Decker.  These manual planning systems utilized Fixed Lead Times for purchased parts and a combination of fixed and variable lead time elements (fixed move, queue, setup and variable run time per unit) for the manufacturing lead times of make assemblies. Mfg. LT = Move + Queue + Setup + (Order Qty. * Run Time per Unit).

A week after being walked out the door due to the 1975 recession I found employment again in Columbus, as an Inventory Control Analyst (Shop Floor Scheduler) for a heavy equipment manufacturer of electric driven coal mining machinery.  This company was in business since the late 1800’s and it was there I found the manual planning process that preceded computerized MRP planning.  It was a complete manual MRP planning process utilizing Acme Visible index cards with lots of clerks running around posting entries to transactions.

I had to be totally retrained by some senior schedulers who wore green cellophane visors as headwear and striped long-sleeved shirts with arm bands.  I thought to myself that these were the type of schedulers who planned the production of the bombers of WWII and the 1957 Chevy Bel Air.  Wow!

There was one retraining session that will always remain in my mind.  The senior scheduler was judiciously studying one of his ledgers and said to me “Here, we have to create two manufacturing orders for this gearbox assembly, a 10 piece order for final assembly and a 5 piece order for a spares requirement.  They are both due on the same due date but we have to release the final assembly order on June 1^st and the spares order on June 15^th”.

I questioned him and asked since the orders were both for the same gearbox and due on the same date, why not set the release dates the same for both orders?  He stated that the orders were for different quantities and releasing them both on the same date would unnecessarily overload the broaching and Bridgeport machining operations.  He was doing CRP in his head!  He was also using the true manufacturing lead time elements of move, queue, setup and runtimes so the smaller quantity spares order could be released at a later date than the larger quantity production requirement.

The most important lesson I learned from the senior schedulers was the impact of the accuracy of the true manufacturing lead time elements to the success of the overall schedule.  The lead times elements had to be accurate with as little padding as possible.  Too much padding and you will overload limited resources and start the jobs too early along with bringing in purchased material too soon thus inflating inventory levels.  Too little padding or lack of lead time would release the jobs too late and not give the shop floor enough time to complete the orders on time.  Too little manufacturing lead times also schedules the purchased materials in too late and then when the informal shortage meetings are held you are in a constant expedite mode to move up the jobs on the shop floor and pull in the purchased material.

Stay tuned for part two tomorrow where I’ll discuss Manufacturing Lead Time Overrides.

What I really like about the quote though is the combination of a realization about life, followed by a radical shift in behavior.

As importantly, from an operations perspective, is that the quote the neatly captures two really important concepts in planning, namely:

• How certain are we that the plan represents reality accurately?
• How will we behave when we know the plan is never accurate?

Life is Uncertain

Years ago, I had an on-going discussion with a colleague about the importance of uncertainty in any model.  The topic was about how likely it was to achieve a plan generated by a model. Think of likelihood as a measure of the accuracy of a plan. It turns out that the likelihood is scarily small, and gets smaller as the time horizon expands. Correctly, my colleague said that people wanted certainty; they didn’t want to know that it is unlikely that they would ever achieve the plan they put in place.  He is correct in that people don’t want to know this, but incorrect that they shouldn’t know this.  They should know and develop different competencies and skills.

We all need to plan. That the plan is not 100 percent accurate is not the problem. The fundamental problem is that we behave as if the plan is 100 percent correct.  This is manifested in the fact that we even develop metrics such a ‘Plan Conformance’ or ‘Plan Adherence’, and measure our factories and supply chains as if these are attainable. How silly is that?! Einstein’s definition of insanity is Doing the same thing over and over again and expecting different results. If we know that the plan is never 100 percent correct, why behave as if it is?  Why not also develop the competencies and skills to respond profitably and quickly to real conditions, which often don’t match what we anticipated through our planning process.

I believe that ‘uncertainty’ is a more fundamental concept than ‘volatility’, in Operations in general, and in supply chain specifically. Clearly Ernestine Ulmer would argue that uncertainty is a fact of life. Industry/market trends such as demand volatility, globalization, escalating customer expectations, shortening product lifecycles etc… only serve to amplify the underlying uncertainty. But uncertainty was always there whether for demand, capacity, quality, supply, lead time, or any number of other factors that go into the models used to create plans for our companies. The most succinct way to capture the result of this uncertainty on these models is GEP Box’s quote that

“Essentially, all models are wrong, but some are useful.”

Uncertainty and the consequent model inaccuracy are themes I have been writing about for some time, including my latest blog and in terms such as “embrace volatility”, “embrace complexity”.  Complexity and volatility only exacerbate the fact that the model is inaccurate and therefore the plan is inaccurate.

Eat Dessert First

If I were to define a tag line for Kinaxis, it would be “Plan, Monitor, Respond.”  The importance of this line is the implied equal importance of these three competencies in tandem.  This is a very important shift to recognize the importance and value of being able to detect quickly when and where the plan does not intersect with real life, and then be able to respond quickly and profitably. It is not enough to develop world-class planning skills in isolation. We must develop the competencies and skills to reduce the time to detect that our plans will not be realized, and the competencies and skills to reduce the time to correct by demand or supply shaping, or by modifying our plan.

This is a big change in approach because in life it seems unnatural to anticipate the worst and to change our behavior accordingly.  When we teach our kids to ride bicycles we teach them how to stay on the bike, not how to anticipate when they are going to fall off and how to roll when they do, so that they hurt themselves less.  And yet, we buy insurance to cover medical bills in case they fall and break an arm.  This behavior is predicated on the assumption that all kids can learn to ride bikes well enough so that in nearly 100 percent of the time they will be able to ride their bikes without incident, and insurance is there to cover the 0.1 percent of the time when they fall off. In other words our behavior is predicated on the assumption that our kids will only injure themselves very occasionally.

How would we behave if our kids fell off their bikes 30 percent of the time they went riding? What if they fell 50 percent of the time? One natural response is to teach them to ride better and therefore fall less frequently. How would we respond if after 10 years of trying, they were still falling off 30 percent of the time they rode their bike? (I reference the Terra Technologies study on forecast accuracy in this context.) Would we not at some point want to teach our kids to anticipate when they are going to fall and how to fall to minimize injury?  One logical response is to tell our kids that they cannot ride a bike, but that isn’t possible in the real supply chain world.  So aren’t we duty bound to teach our supply chains not only how to ride better, but also how to anticipate that they are going to fall, how to fall gracefully to reduce the likelihood of major injury, and most importantly, how to quickly get back up and on the path?

But the highlight for me was the Influencer Panel I hosted as the last event of the conference.  We had great participation from:

• Andy Coldrick of Ling-Coldrick
• Bob Ferrari of The Ferrari Research and Consulting Group
• Russell Goodman of SupplyChainBrain.com
• PJ Jakovljevic of Technology Evaluation Centers (TEC)

While all the panelists added greatly to the discussion, two highlights for me were comments made by Andy and PJ.

Andy said that we have moved from thinking we need a single number forecast (and therefore single number plan) to understanding that we need a single perspective and a range of plans that cover range of possible business conditions under which we will operate over the next period. My take on Andy’s point is that “what-if” analysis is an absolutely core capability at every level of planning, be that strategic , tactical, or operational.  Being able to understand what levers are available to you and the impact that pulling these levers will have on financial and operational metrics is crucial to developing flexibility and agility in your supply chain and broader operations functions.

PJ used the dramatic failure of the Boston Red Sox in August to illustrate that planning is not enough.  As PJ told it, the Red Sox had done a tremendous amount of planning over the past few years which is what resulted in their great season up to August.  But what management failed to do is monitor the health of the star performers and only realized that some players had put on as much as 15 lbs.  Even worse their mechanisms for responding were not in place meaning that they had no way of getting relief pitchers or other key players at such short notice. PJ’s anecdote captured my view that planning is not enough very well.  It also ties in very well with Andy’s observation about a range of plans.

How Andy’s and PJ’s comments link together is that you need to monitor how your operations, particular customer demand, are matching up with what you anticipated (your operational plan), and respond very quickly when the two do not match.  Having pre-evaluated a range of possibilities means that you are able to respond with confidence, even though reality will never quite match any of the scenarios you had pre-analyzed

Planning is not enough, but we all have to do it. Not planning would be very stupid. But not building the capabilities to detect when reality does not match the plan very quickly and then respond profitably to reality is equally short-sighted. Plan-Monitor-Respond.

What we are most proud of is that this is a customer-driven award – multiple nominations from our customers is what landed us on the list. We are humbled.  A very warm thank you to everyone who submitted on our behalf- whoever you may be!

You can check out the entire listing here.

And while you’re on their site…

…check out a great video called, “S&OP: What’s It Really About?” featuring Trevor Miles, director of thought leadership here at Kinaxis. In this video (free registration required to view) Trevor provides his thoughts on why so many companies seem stuck in the early stages with their S&OP efforts, and how they can move up the maturity curve to realize significant performance breakthroughs.

Source: http://www.gartner.com/it/content/1393400/1393424/august_18_supply_chain_jbarrett.pdf (page 17)

What I find most interesting in the Next Generation S&OP is implied, but not stated explicitly. That is that Integrated scenario analysis, Supply “what-if” and Base supply plan (in nine-step S&OP) are replaced with Supply “what-If”, Financial “what-if”, base supply plan and base financial plans.  What I believe is implied is that:

• Integrated scenario analysis, which was looking at just the supply plan, is extended to include a financial plan.
• The next generation approach will be much more interactive and integrated so that the financial and operational impacts from alternative demand or supply plans can all be considered (easily) in the S&OP process.

The diagram below is an attempt to show the evolution of the development of an integrated consensus plan which addresses and balances the interests of demand, supply, and finance.

In the “new world”, managers can see supply, demand and financial projections based on the current or potential supply and demand plans. By seeing the impact of change, they can develop a new “consensus plan” which represents the best balance between competing objectives.

My colleague Trevor Miles wrote a very interesting piece a while back called “IBP or S&OP: What’s in a name?” Check it out and provide feedback below.

Although there may be no such thing as a perfect forecast, there are plenty of opportunities for improvement and managing demand in support of a more cost-effective supply response. Better collaboration between trading partners is the necessary next step toward waste elimination in the value chain.

Maximizing value from the supply chain won’t be reached without improved collaboration between trading partners.

In fact, Mike identifies the lack of collaboration between trading partners as the primary cause of demand volatility. (I agree that the lack of demand visibility increases demand volatility, but there are other industry dynamics that are increasing demand variability.)  Of course, visibility and collaboration are the key messages behind The Beer Game (or beer distribution game) which was originally invented in the 1960s by Jay Forrester at MIT as a result of his work on system dynamics to illustrate the bull-whip effect.  Absolutely critical to a smoother functioning supply chain is demand visibility across the entire supply chain.  Of course visibility isn’t a very mature form of collaboration, but it is at least a start and a necessary precursor to more mature forms of collaboration. And let’s be honest, after 50 years we still haven’t really got to effective demand visibility, although there have been improvements.  To get some estimate of how well your company is performing in this regard you can take the Gartner Demand-Driven Value Network (DDVN) maturity self-assessment.(Registration or Gartner membership required.)

But it isn’t just so-called Easy-West collaboration between customers and suppliers that is required.  I would be happy to start with the so-called North-South collaboration between strategic and financial plans, usually the focal area of the executive suite and Finance, and operational plans. Some analysts and commentators have called this integrated business planning, which also dates in concept from the 1960’s. I’d even settle for East-West collaboration between demand and supply functions within one organization, including Gartner’s stage 4 Sales & Operations Planning (S&OP) maturity. There is no inter-company process that is a better measure of collaboration than S&OP done well.  According to Jane Barrett of Gartner, most companies are stuck in stage 2 maturity.  This is largely due to the inertia and resistance to change so prevalent in many companies.

But how is it that 50 years on from Jay Forrester’s work we are still struggling with this issue? My opinion is expressed in a blog titled “Do you trust yourself to collaborate? The real barrier to collaboration is not technology, but trust”.  Let’s face it, technology can always be improved, especially the user experience. But the capabilities of the technology available for inter-company and intra-company collaboration exceeds the willingness of organizations to share information at the moment.  As Mike Burkett points out, huge gains can be achieved by collaboration, so why don’t companies try to capture these benefits?  My opinion is that the issue is the same that is preventing them moving from stage 2 to stage 3 S&OP process maturity, namely that they simply want to automate their existing manual processes and don’t realize that effective collaboration requires both new ways of working and supporting technology capabilities. 

Nothing captures this better than a Henry Ford quote that “If I had asked my customers what they wanted, they would have said faster horses.”  There is a strong synergy, even symbiosis, between technology and process.  In a great slide show titled “What if Peter Drucker taught Enterprise 2.0?”, Mark Fidelman states that

Neither technology nor people determines the other, but each shapes the other.

But let us recognize that the financial and operational risks of collaboration are tangible and can be high.  There is a good series on collaboration in the Harvard Business Review.  The one I like best dates from June 7, 2011 and is titled “Collaboration is risky.  Now get on with it.”  The author, Whitney Johnson, writes that

Why is teamwork so difficult?

Because collaboration is actually a pretty risky business. Perhaps, like me, you are generally of the mindset that two heads are better than one. But because your ideas frequently get co-opted, there’s a risk-reward imbalance that makes you reluctant to engage. Or maybe you’ve reached out to a potential collaborator only to have your lack of expertise exploited. So, rather than ever again experiencing the one-two punch of ignorance and vulnerability, you’d prefer to soldier on alone. In both instances, the fundamental barrier to collaboration is a lack of trust.

While writing about individuals within a group, clearly Whitney’s observations and opinions are very applicable to collaboration between functions and organizations.  Her prescription is to

1. Start with simple exchanges where the cost of betrayal is low.
2. Remember that our collaborators are competent.
3. Don’t take advantage of our collaborators’ deficiencies.
4. Give others their due, and expect yours in return.

Sound advice.  Yet so difficult to put into practice.  The comments section is well worth a read too, including links to some interesting materials.

Mike Burkett concludes his First Things Monday contribution with the observation that

By closing gaps between partner nodes in the supply chain, there’s an opportunity to address the unnecessary waste across the value chain.

These are the hard benefits of supply chain collaboration.  They are real and they are achievable.  Yes, the risks are real, but the rewards are equally real.

Companies with mature S&OP processes testify to the predictability and transparency it brings to the business. While neither the process nor this revelation is new, the fact is that two-thirds of businesses do not progress beyond the first two stages of Gartner’s 4-stage maturity model.  This complimentary Gartner research report provides recommendations for achieving higher stages of maturity, and highlights the benefits of doing so.

Download the newsletter here.

Is your company facing a growing urgency to derive greater value from your S&OP processes?  What are the steps you are taking in response?

To get started, let’s get beyond the nuance of the debate. This debate is not about the TERM. I REALLY don’t care what term is used or what process is called. I agree with Shakespeare, “A rose by any other name would smell the same….” But, I don’t agree with the conventional views on Integrated Business Planning (IBP) in three areas: focus, emphasis, and readiness.

Basically Lora argues that IBP is simply sophisticated S&OP. I’m not sure I agree. I think this characterization misses some subtleties between the two terms. Let’s start with Lora’s argument:

The number one change management issue with S&OP is and continues to be the role of the budget. If the company wants to maximize opportunity, the budget should be an input into the process, but not constrain the process.

Yes, I agree, but this is looking at the issue from the wrong perspective. What is broken is the budgeting process, which should be a continuous process driven by the operations forecast.  And there is a lot of discussion in the Financial Planning and Analysis (FP&A) space about this, starting from an article titled “The Inherent Folly of Cash Forecasting” by Gavin Swindell in BusinessFinance. Gavin states that:

… The Hackett Group, recently published a survey of CFOs, and 70 percent rated cash flow forecasting as their top priority to be worked upon in 2011. Now, maybe I am being a little simplistic, but I find this strange.

Gavin argues that cash forecasting should be a “dependent” forecast based upon the operations plans for demand and supply. In fact he states:

The point is there is no need to forecast cash in a well-run business. It should be calculated. Anyone who is applying serious effort or cost to do so is papering over a business weakness presumably because they feel they have to or because they cannot fix the underlying causes. In many businesses, the cash flow from operations and the inherent working capital will week in week out account for the majority of transactional volume and value that businesses find hard to plan and predict accurately.

I agree. As importantly so do many others, for example in CFO Russ Banham states in a blog titled “Let It Roll” that:

Unilever parted with its annual budget in 2010, with no tears. So did Norton Lilly International. Statoil and American Century Investments have scrapped their budgets; others are expected to follow suit.

Russ is arguing that the annual budgeting process is broken and needs to change to a rolling process, and gives as an example Unilever which has moved to a quarterly budgeting process with a forward view of eight quarters. Russ has a great quote from Statoil:

Statoil, the large Norwegian oil-and-gas producer, decided to abolish the traditional annual budget in 2005. “We still do what the budget unsuccessfully tried to do for us: target-setting, forecasting, and resource allocation,” says Bjarte Bogsnes, vice president of performance-management development. “We used to try to force these three purposes into one set of budget numbers, which created serious problems. For example, how can you expect an unbiased sales forecast from a sales manager if that number also will become a target? And how can you expect unbiased cost or investment forecasts from the organization if those forecasts also serve as an application for resources, and everybody sandbags?”

Who am I to disagree when even the McKinsey Quarterly in an article titled “Just-in-time budgeting for a volatile economy” published in the Spring 2009 edition in which the authors, when commenting on the budgeting process, state that:

Managers often spend significant amounts of time on it, only to be dismayed by how little value comes from four to six months’ effort. Under volatile conditions, when economic forecasts change from week to week, developing one reliable budget to coordinate business units and track performance for an entire fiscal year is very difficult. Following the traditional budget process may even be unproductive.

In fact they argue that the budgeting process needs to include the following:

1. Scenario planning with trigger events
2. Zero-based budgeting
3. Rolling forecasts
4. Quarterly budgeting

Perhaps even more importantly budgeting as part of FP&A covers a lot more than demand/supply balancing, which is the cornerstone of S&OP. Lora may argue with me that a mature S&OP should include much of what I discuss above, which is true, but the breadth of S&OP does not usually cover workforce management, R&D spend, capital expenditure, indirect procurement, and a whole host of other areas of interest to the budgeting process.  Perhaps the most important of these is workforce management because so much of a company’s cost base is salaries for it employees. Deciding how many people should be in Marketing in a certain region should be based upon the forecast for that region. The manner in which the Marketing budget is spent should depend on the make-up of the projected revenue for that region. The same is true for Sales and Admin, Procurement and Warehousing, etc…

Bringing all of these different cost elements together based upon the revenue forecast is integrated business planning, whether we call it IBP or not, and has a much wider scope than does S&OP. But, for all the reasons others have given, the budgeting process should be driven by the revenue forecast generated as part of the S&OP process, not the other way around.  And of course adjustments to the S&OP plan may need to be made because of financial constraints that force, for example, a delay in hiring in R&D or expenditure on capital equipment, which impact the revenue projections.

Lastly supply chain management (SCM) is very manufacturing focused and, as a consequence, so is S&OP. Of course we can talk about SCM in Retail, but the heart and soul of SCM is manufacturing. So what is the equivalent of S&OP for say a Financial institution or a consulting organization? What about bio-pharmaceutical companies which while still having large manufacturing divisions are primarily focused on research and development on one side and sales and marketing on the other side, which is reflected in the fact that their cost of goods sold is often less than 20 percent of revenue and Selling, General and Administration can often be more than 40 percent of revenue? I’m not convinced that S&OP is sufficient to run these organizations optimally.

So I don’t think IBP is simply sophisticated S&OP. So who do you agree with: Lora or me?