“I do solemnly swear that I will faithfully execute the Office of Demand Planner…”

Often referred to as the bellwether of an administration’s potential success, the first one hundred days of a presidency are scrutinized by political pundits. The importance stems from extrapolating trend – something demand planners can relate to. After all, if the first steps are taken to the east, when the expected route was to the west, confidence can wane – along with crucial success elements like trust, reliability and momentum.

So what trends does a demand planner hope to establish in him or herself when embarking on a new employment journey? Just like the President you can’t go it alone, and wise planners know that they wouldn’t want to. You need folks to want to work with you – it’s not a demand planning monarchy (as fun as that is to think about).

Drawing on another parallel, demand planners strive daily to steer business conversations from a ‘past predicts the future’ approach to a  ‘manifest destiny’ shaping approach. A demand planner should also develop expectations for their work based on their experience and how their colleagues operate so they can shape how they will add value and create new, expanded notions of what is expected of them.

My advice to demand planners in the first critical days and months in the job is this: operate with intention and be thoughtfully preparing yourself for your first ‘State of the Union’ address (which we in business refer to as the less sexy “performance review”) from the onset.

Seek To Understand Before Being Unemployed Understood

Step 1: Personal Reflection

Take stock of your own past experiences – the good and the bad – and set your course based on the old ‘start, stop, continue’. What worked well in your prior roles? What didn’t? Knowing these allows us to start positive new behaviours, stop old negative behaviors and continue doing what works.

Demand Planners classically fall into INTJ (introverted, intuitive, thinking, judging)  profiles. [Ed: This is one of Carl Jung’s personality types.] Are you aware of the strengths and limitations of your own personality type?  If not, research it. “Know thyself” is an important mantra when it comes success in business, not least because it helps us understand how we are viewed by others.

Approachability trumps aptitude. Empathy beats intelligence. Insights win over ideology.

Approachability trumps aptitude. Empathy beats intelligence. Insights win over ideology. And energy can overcome a range of limitations. You might be revving to jump on data or knock socks off with your problem solving abilities but don’t lose sight of why more Sales people typically make it to leadership roles – it’s because they’re liked. Be likeable, be humble, be bright and be on-point.

Be likeable, be humble, be bright and be on-point.

360 degree feedback surveys to former co-workers are an excellent idea and free online tools like SurveyMonkey make it a breeze. Just remember that feedback is a gift, so don’t get worked-up if you don’t like every response – try to look at it from each contributor’s lens of experiences with you, what their personality styles are, and how you can start, stop or continue certain approaches and behaviors. This way you can leave behind what didn’t work and keep what does so you can better handle future interactions.

Step 2: Map Out What You Do & How You Do It

A methodical approach should start with being thoughtful about your method. If you’ve got your “how” (to work effectively with people) solidified from reflection, now you need to define your “what” (the heck to build an understanding of).

Here’s the Schneider Method for defining your knowledge assertation plan of attack:

1. What do we do
   • Process mapping
2. What do I not know that we do
   • Voice of customer – VOC
3. What do I have that helps me do what we do
   • Compiling existing knowledge
4. What do I not have, but know that we do
   • Gap analysis
5. What can I do, to help myself & others do better at what we do
   • Action Plan

Within each of these exists the classic elements of People, Process, and Technology. Build-out questions before you start your first day at the new job and spend the end of each day recording what answers you found, curating relevant/related resources, and adding new subsequent questions (to circle back on). An example of “What do we do” is as follows:

People: Who do we presently collaborate with on consensus forecasting? Who consumes information from our team? Who are the decision makers by customer, location and product (or service)?

Process: What S&OP process do we support? With what frequency do we publish our plans and are they subject to any planning fences? What elements of CPFR, statistical modeling, scenario planning, and override incorporation are present?

Technology: What tools are we using? Where does the data come from? What transactions and filters are included in our demand history arrays?

Supplemental questions should spring easily from these – give a free mind-mapping tool a try under each category and try to keep each category rounded out for equal attention.  Things like differences in organizational designs across the matrix of collaborators, what costing method the company uses, and what internal financial calendar behaviors come into play in the fiscal year and when etc.

Step 3:  Diagnostic & Descriptive

As Malcolm from Jurassic Park would say, “That is one big pile of …”.  Data is messy at all companies. Suck it up, buttercup. In fact, get excited about it! A planner is only as good as the information he has to work with and build insights from, so embrace the opportunity to demonstrate your skills as a data architect and analyst (someday a data scientist – see the Winter 2017 JBF for more thoughts on where that’s heading).

Data is messy at all companies. Suck it up, buttercup.

The biggest “seek to understand” opportunities in the first one hundred days come from getting intimate with your data. Locate every master table from your ERP system you can – product/material, customer, location, etc. Pivot and slice them and couple with meet and greet interviews, learning what fields matter, what they are synonymous with and how they are structured (hierarchies, relational data sets, interdependencies – i.e. fields that may be rules-based and derived from others). Simple ABC pareto efforts and density charting (pie charts, scatter/bubble, map-plotting) should help you build a strong, early understanding of top customers, products, geographies, and combinations. Going one step further and conducting segmentation on the key material, location, and consumer data elements will bear much intuitive fruit (early and growing, stable, volatile, high value, low value, declining lifecycle).  Study the forecastability of your data elements to demand plan.

Check these learnings with peers and stakeholders as you get a handle on each of them. This will go a long-way towards showcasing your initiative, comprehension and focus.  Remember: Sift, sort, structure, stratify, substantiate.

Step 4:  Prescriptive & Pioneering

If you do what you’ve always done, you’ll get what you’ve always got. Your early learnings should help you begin to understand where to focus your efforts to drive improvement and perhaps introduce some new approaches. Perhaps it’s structuring your efforts differently (planning bills from studying correlations in demand patterns), perhaps it’s changing consumption settings, time series durations/intervals, or moving certain areas to alternate plan & fulfillment strategies (reorder point, make to order).

Wishing you great success on your new endeavor. You are to be a trusted advisor, a master of lean planning pursuits, a grounding force against bias, and an ever-inquisitive scientist. Plan on!

The Friendly Neighborhood Forecaster

“30% forecast accuracy? Seriously? What do I pay you for?  I could flip a coin and get better results than this!” Yes, we hear this as demand planners. And yes, it hurts – deeply, personally, unjustly.

It’s one of the most frustrating and demoralizing feelings as a Demand Planner to know that you’re trying your darnedest to improve the accuracy of something which you know is largely unforecastable. You’ve maxed-out modeling and model-tuning and have resorted to fishing for any judgemental recommendations that you can get your hands on. The latter likely only helping to see accuracy further struggle with snowballing bias and negative FVA of compounding “expert” overrides. Having thrown everything but the kitchen sink at the problem, you shift your efforts to building-up verbal defences with a Pixar-worthy storyboard of empathy-seeking data challenges and culpability-shifting anecdotes. If only there was a way we could prove to management that this product is not actually forecastable….

We Need To Set Management’s Expectations About What Is Forecastable

Management may be aware of standard forecast metrics – many are introduced in MBA programs, SCOR and Operations textbooks. But typically executives are more worried about how quickly they can show improvement in these measurements than how they are calculated.

Similarly, as demand planners, we are trained and certified on the most common algorithms, performance measurement computations, and off-the-shelf forecast modeling data structure requirements. If we are to set expectations about what is actually forecastable, and what we can actually achieve as demand planners, we need to look beyond these basics. If we don’t we will forever be taking unfair criticism for things outside of our control. What we need to do is not only present our forecast accuracy, but present it alongside forecastability. Forecastability reveals the extent to which an SKU can be forecasted, and provides the crucial context for our forecast accuracy.

Forecast accuracy depends on how forecastable the product is.

Questions To Ask To Gauge An SKU’s Forecastability

What change in forecast accuracy is realized when the best-fit model is recalculated from different assortments of time series horizons?

Are the changes more prevalent for certain model types (hint – they should be for some, especially for more factor-inclusive model types like exponential smoothing)?

What differences in forecast accuracy are observed in monthly, bi-monthly, and quarterly period bucketing?  (Is poor forecast accuracy at the monthly level dramatically improved if consumption and forecast accuracy are looked at in quarterly buckets instead?)

Are any SKU-to-SKU, product line to product line, and product family to product family correlations observed when regression comparisons are run to look for like patterns in the demand history?  Are any of these like patterns accounted for in existing planning bills or bills of materials?

What record counts and financial weighting do the products and model types comprise when categorized into basic segmentation schemas (high value, volatile; high-value, stable; low-value, volatile; low-value stable)?

What are the historic forecastability ranges, within each segments and per product families? (Note: Segmentation can be combined with ABC and Pareto analyses, as well as calculated for markets, customers, or for products within each market/customer.)

Within low-value, volatile records, is inherent demand variability such that the cost of error is more prohibitive than a simple order policy (ex. reorder point or make-to-order)?

By asking these questions, we gain an insight into forecastability – what can be forecasted accurately, and what cannot. We will be able to go the S&OP executive meeting, or sit down with Sales and Marketing, Finance or senior executives, and be able to say with confidence that for a particular SKU, 30% forecast accuracy is a good thing. We can explain why an SKU cannot be accurately forecasted and then make suggestions based on that – after all, knowing that demand for a product cannot be predicted has serious implications for the business. Knowing this allows us as demand planners to mitigate risk and propose the best course of action.

What’s more taking the time to understand what one can forecast and what one cannot, and what results can be expected, one can set better expectations and understanding upfront.

How To Prove That 30% Forecast Accuracy Is A Good Thing

In the opening example, proving that 30% is actually a job well done given the forecastability is important (try re-calibrating your BI tools to show forecast accuracy in terms of variance to CoV). Go one better by showing that the cost avoidance of whatever initiative is actually outweighed by the cost of forecasting for it. If you communicate that the ‘juice-isn’t-worth-the-squeeze’ you can get work off of your plate, allowing you to focus on what matters.

Variability can be lessened by extending the time buckets planned for (daily to weekly to monthly to quarterly to semi-annually), but it is more costly. In certain markets and in certain products, this may be the only option and one that demand planners should constantly be evaluating and influencing. On the flipside is also finding ways to try to improve forecastability by forcing the square peg to better fit into that round hole.

For example, CoV movement over time can be tracked. Where increasing, investigations can be conducted to identify with Commercial colleagues the causes and then the script flipped to challenge what can be done to shape back. Analyzing positive correlating 4P’s effects in more stable products can sometimes yield a playbook to try for your more volatile areas.

Parting Thoughts On Forecastability 

This friendly neighborhood forecaster’s closing reminder is this: You measure how something is setup to execute, and you measure to control or to improve. But if the setup is wrong for the metric, or the metric is wrong for the setup, then you’re allowing the box that you’re in to dictate your success. Break out of the box, see if you need to redesign the box or redesign the metric. In forecasting, one size does not fit all – don’t let spinning on the wheel stop you from asking the question “why?” more often. That is how we understand what is actually forecastable and what isn’t, how to get the credit we deserve, and push the discipline forward.

Stay inquisitive, my friends. That’s the mark of the best Demand Planning professional.

Excel is Excel, right? Vlookups and Pivot Charts provide everything I need, so why would I upgrade to Excel 2016? If you are asking yourself this then boy, you are in for a treat! Your friendly neighborhood forecaster is going to share something very cool about Microsoft Excel forecasting.

Valuable Tools To Forecast In Excel

Like many of us (and I’ve seen the surveys), there’s a good chance you do your forecasting in Excel. If you’re one of these people, or you have a forecasting tool but also want to do your own supplemental modelling once in a while, then get ready for a shocker! There are new, surprisingly unknown forecasting features that were launched with Excel 2016, and they were included for free!

Now before I jump into the cool new stuff, let’s establish some baselines. If you’ve never built a forecast in Excel before, consider yourself blessed and thank your employer for wisely purchasing demand planning software with a stat. forecast engine. Then take some time to look around and acquaint yourself with the basics of Excel.

Forecasting in Excel is a great place to start if you know all the tools it offers

Recommended Books for Microsoft Excel Forecasting

The best resource is the IBF’s primary source literature, Fundamentals of Demand Planning & Forecasting, by Dr. Chaman L Jain. It is mandatory reading if in you’re in this profession, in my opinion. I’m just a blogger, but you came to read me, so why don’t you just trust me and buy it! Also useful (and well-worn on my bookshelf) are Forecasting Methods and Applications by Spyros G. Makridakis,‎ Steven C. Wheelwright and Rob J Hyndman, and Excel Sales Forecasting for Dummies, by Conrad Carlberg. The latter also has a useful cheat sheet available online.

Buy the books, read, go play with Excel, then be brave and make a few forecasts and see how they did. Make sure to use holdout periods.

The Little-Known Excel Forecasting Tools

If after experimenting with Excel’s Data Analysis add-in and the basic Forecast, Linest, Correl, and Trend functions, you find yourself feeling confident but still yearning for the fresh-stuff teased by this blogger, then come try your hand at this:

Present in the Ribbon in Excel 2016 under the Data tab, is a new section literally called “Forecast”. The Forecast Sheet is a dead-simple option that allows users to highlight a data set with two series – time and values – and generate both a forecast (you enter the desired end date for how far out to extrapolate) and a linear chart.  So simple your boss could do it! There is also an Options section where you can customize things like where in your time series data to start building the forecast from, the confidence interval, seasonality intensity, how to handle missing data points, generating forecast performance statistics, and other tweaks.

Click the Data tab then select Forecast Sheet to set Confidence Intervals and Timeline ranges

The new, behind-the-scenes individual functions of this beautifully simple feature include:

• FORECAST.ETS,
• FORECAST.ETS.SEASONALITY,
• FORECAST.LINEAR,
• FORECAST.ETS.CONFINT,
• FORECAST.ETS.STAT.

Microsoft has a wonderful write-up on the new Forecast Ribbon features and these associated functions, as well as a sample workbook with which to try them out.

Well, that’s it. Not a long article this time, but I bet you that you’ll be thanking me once you try it. I can’t take the credit (thank you, Microsoft!), other than for passing this along. I’ll end with a line from my children’s favorite new Disney movie, Moana: “You’re welcome.” Happy 2018 from your friendly neighborhood forecaster!

Any questions about Excel forecasting, post in the comments section below and I’ll do my best to answer them.

Hearing these words from a superior can be enlivening… or startling… or both.

In the still-evolving world of Sales & Operations Planning — a world of theory, studies, perceptions, and perspectives — many champions see the investment of personnel as the biggest predictor of success. While executive sponsorship is often cited as the most important ingredient, to be successful, implementing a process like S&OP takes human resources; there is no way around it.

Every function in a business, including demand, supply, finance, marketing, sales, management, engineering, participates in S&OP. When asked if dedicated resources from these functions are necessary to support S&OP, many consultants will tell you “it depends.” I like that answer, because it reminds me why consultants make so much money. It depends means “I’ll tell you that if you hire me to consult for you long enough, I will get to see and learn your business and make an informed decision.”

For those with finite funds, I’ll give you the secret learned later in these lengthy engagements. Are you ready? Effective support for you S&OP process, absolutely, takes full-time resources. We will get into why full-time, how those resources differ from the still-needed part-time participants, and where to find them.

OK, so if you’re a fan of S&OP — you’ve seen what it can do — then hopefully I’ve got you excited. I want you to be able to take this article to your boss, lay it on top of the other S&OP white papers, and finally hear those words that opened this masterful piece of blogature — “Go hire.” Well, if your boss is enraptured, giving what you / they want comes at a price — like anything (perhaps I do have a future in consulting!). That price is that S&OP resources must be some of the most skillfully managed talent that your firm employs.

S&OP is frequently instigated and implemented by Supply Chain — so in most undertakings, its success or failure depends on how well this function minds the embers, feeds the fire, and fans the flames. Finding the right captain and the right lieutenants takes an understanding of what true talent in this area looks like. Beautifully summarized and borrowed with permission from Robert Bowman at SupplyChainBrain is the following excerpt from a few years back:

Companies say that they are in dire need of competent supply and demand planners, but the requirements of that position today are so varied that you wonder whether a single person exists who can do the job. It calls for strong math and statistical skills, obviously, but a good planner must also be able to communicate well across the multiple silos of an organization. The right candidate will have a deep understanding of the requirements of manufacturing, logistics, marketing, sales and finance. Then there’s the necessity of reaching outside company walls to suppliers and customers, to ensure that all parties are in agreement about what the demand forecast should be. Who are these freakishly talented individuals? And where can they be found.

I hope that this hits home for some. If you are a professional in Supply Chain in 2016, then you should be extremely proud. Even without the order and structure that S&OP affords, the essential thrusts it implores — running by the numbers, searching for insights, influencing sound decision making — are all expectations of the demanding daily work of Supply Chain in this fast-paced, globalized business world.
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Development of individuals for planning roles is paramount. Adding more planners because of a new product family addition or departmental workload leads many companies into trouble. Few Supply Chain planners study this discipline and jump right into it; most fall into it over time. Therefore, varied foundational experience and education can leave doors open to evacuate for these individuals, if sustained role interest, perceived value, and future opportunities are not afforded.

Greater than resource capacity planning, the most important role of H.R. in S&OP and Supply Chain management is helping the business to formulate adequate strategies for talent development and retention. While talent loss is costly for any role in a firm, losing experienced individuals who have developed intimate understandings of products, personalities, patterns, and plans is even more so. Be strategic. Turnover in this space is avoidable, and the elevation of the importance of these roles starts with education.

Circling back to dedicated S&OP roles, managing a process that has both tactical and executive layers takes a lot of time and a lot of talent. Developing the demand plan, evaluating supply capabilities and constraints, exploring financial solvency, integrating commercial sensing and shaping, and unlocking leadership expectations — every month — cannot be done as part of anyone’s “normal” job. For S&OP owners, this is the job.

These roles not only own the design, execution, and continuous improvement of the milestone executive S&OP monthly meetings (4-6, depending on philosophy), they also manage and lead the daily and weekly tactical meetings that explore and link SKU, account, and regional details. Engagement must be fostered, maintained, and the future talent needed to continue to evolve S&OP has to be ripened. As supporting leadership to the owner, full-time S&OP coordinator roles are further suggested to lead and ensure accountability within demand, supply, and finance; each with similar, function-specific, expectations like that of the owner.

S&OP positions are the best of the best in the participatory functions. Some individuals should be put on the path for organic growth within their teams, others for possible rotationary development across the functions; but S&OP presents additional opportunities to promote talent with specific intention. As Oliver Wight® asserts, “Coordinators and IBP (S&OP) project leaders often become the next generation of executive managers, and for good reason. Why would you not want to promote the people that have been actively participating in the integrated way of running the business?”

When it comes to S&OP roles, think it through. Investing in staff members, only to lose them because of a lack of strategy, is a bad outcome. Carefully develop the case for the need, plan and educate on the roles and role life cycle planning, and make your S&OP program a desirable place to be!

Want to learn more about what to look for in hiring advantageous S&OP roles or how to appreciate and manage the life cycle of a S&OP program? Join me in the upcoming IBF Webinar: Getting the Brightest & Best: S&OP Talent Management, on August 31st. Plus, you can also join me at IBF’s Business Planning, Forecasting, & S&OP conference in Orlando, October 25-28, 2016.