What used to be an annual spreadsheet event is no longer an option for global businesses that have to navigate and course correct for the daily onslaught of economic, political and environmental events that could derail the best laid plans.

Supply chain complexity is multiplying as businesses become more global and interconnected. To remain competitive, organizations are changing how they source , sell and develop products. The rate of product obsolescence in consumer electronics market alone puts business agility to the test. Add to that the disruption and risk that is part of the volatile global marketplace, and business leaders recognize that the “new normal” is likely nothing like last year…or even last month. Agility is imperative; and it is keeping business leaders up at night.

Next week, On December 7th, I look forward to leading a discussion at the Supply Chain and Logistics Summit in Dallas in a workshop I will be presenting there: “S&OP: Enabling Agility and Flexibility in a Global Organization.” Sales and Operations Planning is the ammunition companies require today to combat complexity, respond to market events faster and manage risks. In this session, we will look at how companies need to create an S&OP plan, ensure that it is executed well so that the desired business performance is obtained to gain profits. In other words, S&OP is not only about the strategy but also about how the strategy can be executed.

I hope to see you in Dallas at my session or at the Steelwedge booth ,#9, to understand how you are addressing business agility in your organization. But even if you can’t be in Dallas, we’d like to hear from you on what agility issues keep you up at night.

Q. If Sales is more focused on opportunity conversion, who should build sales forecast and revenue plan? Is that Finance?

A. Sales should definitely focus on building the sales forecast based on opportunity conversion. Finance should focus on building the revenue plan.

In the near-term, Sales should be able to leverage the opportunity pipeline as a somewhat rationalized basis for the sales forecast. Beyond the opportunity pipeline horizon another basis for sales forecast is needed. Depending on accuracy this can take the form of the marketing forecast, the demand plan or in some cases the stat forecast. This also applies to industries that are not opportunity driven. Whatever the basis, it’s important Sales participates in building the sales forecast and has an ownership interest in it. There is no better way to bake the ‘field’ perspective into the forecast.

To reiterate the point expressed in the webinar, S&OP/IBP should really start at the first stage of the order lifecycle. This will bring greater engagement from the sales team.

Q. You mentioned integrating the Third Party Logistics providers into the S&OP process, could you please share with us an example of this and the benefits achieved?

A. An example of this is industries such as apparel which involve a short life cycle in terms of fashion changes or season changes but also involve offshore manufacturing which results in long lead-times. In-transit inventory plays a critical role in these industries because if the demand for products in the short term is greater or less than expected, any action that has to be taken to balance supply and demand should include in-transit inventory. 3PLs are the entity that have access to the in-transit inventory.

Q. Some relatively new and growing buzz in the Financial (FP&A) crowd is the concept of using Rolling Forecasts versus using the traditional annual budgeting processes.  This process seems more in line with what a traditional S&OP process suggests,  rolling forward forecasts over a 18-36 month time fence.  Thoughts?  Are you seeing client companies modifying annual financial planning processes to a more fluid rolling forecast process for all functions to use (Demand, Supply, Finance, Leadership)?.  (Note:  Let it Roll, Why More Companies Are Abandoning Budgets in Favor of Rolling Forecasts, about organizations including Unilever modifying their current annual processes to a rolling forecast process, seems to suggest that the monthly S&OP output gains much more importance and forces integration.)

A. We agree with this statement – Integrated Business Planning involves taking the output of the process and feeding it to the FP&A process in a rolling fashion. Due to Sarbanes-Oxley regulations we see existing customers adopting some intermediate steps to cleanse the S&OP data and incorporate it into the FP&A process.

Q. If one doesn’t have a time phased price definition, do you still recommend monetizing S&OP using current price and cost? Or is it better to start with a non-monetized S&OP?

A. The answer depends on the industry – are the prices highly variable across time buckets (maybe greater than +- 10%)? If so, then adopting an average price and cost will result in incorrect results. It is better to adopt a non-monetized S&OP in this case. If the price fluctuations are not as high, then we can adopt a current price and cost.

Q. We have a heterogeneous supply side organization, with complex supply networks in some areas and independent supply structures in other areas. On what level should one fix its S&OP process in terms of local, regional or global?

A. S&OP process needs to be driven more by the customer facing situation than the supply side. If there is a need to maintain a single face to a customer across multiple divisions and geographies then it is better to adopt a global S&OP process. If each business division has a separate customer base which is completely different (for instance commercial versus defense) then a regional S&OP process is sufficient.

On the supply side, if there are critical components that are shared across multiple divisions then allocation of the supply should be done to ensure that the material constraints are met.

Q. I want to follow-up on your experience with IBP in non-manufacturing environments. Any cases in upstream oil & gas? If so, which companies?

A. IBP is an effective methodology for any industry. While the measures may be different, the need to align supply, demand and finance is the same. In addition to manufacturing companies we have seen IBP used successfully in process, agriculture and service organizations.

Q: Do we need to have a customer forecast for every customer?

A. No, Steelwedge provides a forecastability analysis wherein we identify the key customers, products and regions for which statistical forecasting has to be done and where collaborative processes could be adopted.

In general, only the high priority customers require a customer level forecast.

Q. How to convince sales force that statistical approach can help versus them dealing with sku level forecasting based on a same-as-last-year approach?

A. It is difficult to convince sales about statistical forecasting approaches. A better approach would be to perform demand policy optimization to identity the SKUs for which statistical forecasting should be done. For the other SKUs, a collaborative process can be adopted with sales involvement. This will ensure that the sales team will focus on the SKUs that require their input.

Q. Can you expand on decisions analyzed by Solver optimization models?

A. Steelwedge provides a solver based approach to perform Rough Cut Capacity Planning versus a heuristic based approach. The following are some of the capabilities and decisions taken:

• Allocation/Supply Balancing – user selectable rules for allocating global demand to multiple markets
• Basic Constraints – lead times, batches, minimums, increments
• Load Levelling – slotting the demand into the gaps in the capacity plan, load levelling forward or back
• Supply Calendars – setting up work calendars for each resource

Q: Much of S&OP is product related. Do you agree that services (which are product-like) too could be supported by the S&OP process?

A. Yes. Any situation that requires the ability to balance demand with supply can be supported by the S&OP process. For example, an engineer-to-order environment supply includes the engineer’s hours available to perform engineering tasks and demand includes custom projects which require the engineer’s expertise.

The game’s goal is for an individual player to score the lowest forecast error for the year. A year-long round consists of 12 monthly “holes” that are scored during each forecasting cycle. Attractive prizes are awarded at the end of the game to those who have achieved the lowest scores (i.e., the most accurate forecasts) to reward participation and focus attention on the importance of minimizing forecast error.

Dr. Kahn stresses the benefits of translating statistical language into more understandable form. For instance, a forecast error of 15% does not readily convey if this error acceptable or not. However, when the same forecast is referred to as “par,” then everyone in the company including other department and management levels can readily interpret that error as being acceptable.

Monthly groupings of sales people into scrambles can further enhance the game by offering someone not doing very well year-to-date the chance to still win, and thus, stimulate players to continue their participation in the monthly forecasting effort.

Rules of the Game

True to the game of golf, Dr. Kahn uses the terms eagle, birdie, par and bogey to describe the possible scores for each hole or forecast period.  The terms describe a forecast’s proximity to actual sales where eagle is extremely close, if not perfect, birdie is very close, par is within an acceptable region of error and bogey is beyond an acceptable region of error.

The baseline forecasts provided by the forecaster serve as par and are typically based on a weighted mean absolute percent error (MAPE). The baseline is distributed to the sales force for adjustment wherein each sales person can accept the statistical forecast or make an adjustment up or down. A player could hold par simply by agreeing to the baseline. The benefit of this is 1) it forces a player to think twice about making adjustments, and 2) it builds credibility for the planner as he/she becomes the focal point of the forecasting process. Ultimately, a sales person should only adjust the baseline forecast if they can improve the number rather than out of a desire to create excess inventory or sandbag for the sake of quota.

The following is the scoring methodology. You can change the particulars to suit your company’s goals.

• Eagle = a score of one. Defined as a weighted MAPE of less than 2.5% and less than the given baseline forecast.
• Birdie = a score of two. Defined as a weighted MAPE of more than 2.5% but less than the given baseline forecast.
• Birdie = a score of three. This is defined as within 5% of the given baseline forecast’s weighted MAPE.
• Bogey = a score of four. This is defined as greater than 5% of the given baseline forecast’s weighted MAPE and less than 10% of the given baseline forecast’s weighted MAPE.
• Double Bogey = a score of five.  This is defined as greater than 10% of the given baseline forecast’s weighted MAPE and less than 20% of the given baseline forecast’s weighted MAPE.
• Triple Bogey = a score of five.  This is defined as greater than 20% of the given baseline forecast’s weighted MAPE.

Yearly awards can be given to the lowest overall score as well as second place, third place and honorable mentions. Forecasting Golf can also include “closest-to-the-pin” during the year (i.e., the person who had the lowest weighted MAPE for a month over the course of the year.)

Extra game components you may want to create could include scorecards and an overall game board. After the first year, handicaps could be considered to even the playing field for those having to forecast products that are highly volatile (e.g., a handicap could be easily calculated by using the standard deviation of actual sales.)

Read the original Journal of Business Forecasting article here.

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What does Sales and Operations Planning (S&OP) mean to you and your company? Do you know if your demand and supply decisions are in sync with your organization’s strategic priorities? Is it possible to align your S&OP process with the big picture without getting bogged down with the many details in the “process”?

Sales and supply chain decision making is complicated – particularly in today’s era of demand volatility and complex, global supply chains. Every stakeholder in the sales, marketing, finance, and supply chain needs to be queried and considered. Forecasts and assumptions need to be checked, particularly when managers are used to relying on past performance and gut feel. You will likely find yourself spending long hours gathering the necessary data before you can even begin weighing the many sales and supply chain trade-offs at your disposal Is this the best way to spend your time? What if you could optimize the process so that you and your S&OP team can quickly and confidently determine the best way forward for your company?

Chris Turner, co-founder of strategy and change management consulting firm StrataBridge, is set to inspire us to stop fretting about process details and dive right into decision-making mode in a webcast entitled “Forget the S&OP Process … Start Making Decisions!” scheduled for Thursday, December 16 at 4:00 p.m. GMT. You can learn the answers to these questions and more when he teams up with John Sookias, Vice President of International Sales and Managing Director (EMEA) of Steelwedge, to discuss powerful ways to connect strategic planning with operational decision making.

In this webinar, you’ll discover how to view S&OP through a lens of the benefits to the business as opposed to the technicalities of the process. Explore the principles of “joined-up decision-making,” driven from where your organization is going, what it will take to get there, and the decisions it will need to confront along the way and learn how to establish “joined-up behaviors’” by making S&OP relevant to people.

This webinar will help you focus on the big picture of S&OP decision making and give you the tools to get buy-in from your executive team. Join our experts as they help you to save your sanity, increase your efficiency, and improve your bottom line!

Click here to register.

Functional groups have unique goals and performance indicators. Sales may be driven to achieve high revenue targets while the Operations group may focus on minimizing labor costs and inventory levels. Finance seeks to manage cash flow, minimize costs and maximize profit. Units of measure may differ from one functional group to the next. Some plan in units, others in dollars. Forecast horizons can vary from current quarter to planning horizon to fiscal multiple year projections.

The key point here is NOT that all groups and individuals should share the same focus and effort. To the contrary, best practice enterprises heavily leverage the unique talents of their employees. Sales sells and Operations drives the supply chain. That said, it is critical that the enterprise has a single, consensus plan that is feasible and all parties agree to execute against that plan. Companies that fail to achieve one agreed plan, are prone to falling well short of optimal inventory levels, customer service targets, availability of desired inventory and company financial goals. A less tangible, but very important by-product of a missing consensus plan is a culture that pits individuals and groups against one another rather than acting as a cohesive team.

From my work at Steelwedge with several clients, it’s been very pleasing to see how the Steelwedge tool promotes cross-functional interaction. Users exchange quantitative and qualitative inputs in an environment that pulls together information in a way that had not previously been available. Beyond data visibility, users are gathering field input, validating assumptions and driving an enterprise plan rather than multiple, isolated departmental plans.

At the end of the day, solutions depend on people, process and technology. If the process and the technology facilitate collaboration, the people become more productive…and happier, too!

An effective S&OP program depends on solid, accurate demand forecasts. Best practice companies do three things well: statistical, top-down and bottom-up forecasting. Many companies are doing one or two of these, but few are doing all three well. Of course, some companies do none. Let’s just say these companies have a huge upside improvement potential.

A statistically generated forecast should use a “best fit” approach to select the mathematical algorithm that minimizes error (such as mean absolute percentage error (MAPE)). The statistical engine should select the best algorithm for each time-phased data series or set of regression data. The resulting forecast should serve as a starting point for bottom-up and top-down forecasts.

Bottom-up forecasts are accumulated from many contributors. A distributed sales force may have hundreds or thousands of contributors. Each contributor has a specific area of expertise such as a specific customer, product or geographic area. The contributor enters her forecasts for her specific area of responsibility. Forecasts from all contributors are summed to capture an overall bottom-up forecast.

Conversely, a top-down approach applies a more centralized view. A small number of forecasters will look at various inputs and generate forecasts. Influencing factors may include market data, economic indicators, and general product and customer trends. Here, too, the statistically generated forecast is a good number from which to start.

The beauty of top-down and bottom-up forecasts is their ability to look at the world from differing vantage points. The folks in the “ivory tower” know important information, but they don’t know everything. The folks in the field have keen insights into their unique areas, but they only see their small piece. The challenge is to capture the small pieces without tainting the field forecaster’s view. In other words, don’t tell the field forecasters the top-down targets. When field forecasters are told what their forecasts are expected to be, they tend to send back values right in line with the top-down values. Such tainted bottom-up forecasts miss the point of gathering field intelligence.

An effective marriage will capture top-down and bottom-up forecasts separately. A management by exception S&OP tool will make comparisons quickly to enable users to analyze critical differences and refine the ultimate consensus driven forecast.