To build a collaborative forecast, you need more than just Marketing, Finance and Supply Chain; you must have Sales involved in the process. They add customer level insights, market intelligence, and real time information that is often not available from anyone else.

Making and keeping a connection with your Sales partners is not easy, but it will pay dividends if you are willing to put in the effort. Here are a few key practices I have used successfully to build a good two-way relationship with Sales that has not only benefited forecast accuracy, but helped Sales drive revenue.

Don’t Assume Everyone Thinks Like You

Never assume Sales is operating with the same “one number” philosophy that Supply Chain uses. Make sure to ask if there are customers being targeted for growth or that are being allowed to decline. You might be surprised to find variances that will provide you with valuable insights that algorithms simply cannot identify.

Do not assume that every person you engage with in your forecast discussions will interact with you the same way, and process data the way you do. Learn Sales vernacular—do they use dollars or units, what calendar period do they compare to, and how do they aggregate their data? Be prepared to modify some of your data to make it user friendly for your audience.

It is important to understand that you will encounter colleagues in Sales who embrace the approach, soak up data, and ask for more. You may have others that are not as enthusiastic to engage and need more time to get up to speed. As you both learn how to work better together, always be clear as to what it is you are looking for from your relationship with them. Do not assume they know what a Demand Planner needs to do their job properly, and vice versa.

It is always good to remind those you work with what the demand forecast is used for in your organization, and how valuable the work done to improve forecasts is to company performance in terms of inventory savings, increased revenue, and customer satisfaction.

Work Hard To Be One Of The Team

Often the personalities of Sales are more extroverted compared to those in Supply Chain—do not let this intimidate you. Show your interest in learning what challenges they face, how they are measured and—equally as important —get an insider’s perspective on your customers. Start by asking to attend sales meetings, customer reviews, planning sessions, and whatever is relevant to your role and available in your company.

As your presence becomes more familiar, and you begin to understand the Sales culture, you can learn what important goals they are working towards, how they are incentivized and, most importantly, they will become comfortable with sharing important insights and keeping you connected. As you build a reputation for being passionate about helping drive the business, you create partnership opportunities. As you build this rapport and establish trust, you can ask harder and more challenging questions, and ask for feedback to make things easier.

In a strong two-way relationship, you need to ensure you are giving at least as much as you are getting. As you build your connections over time, you will begin to get more invites to important meetings, receive more relevant emails, and communications will be less challenging.

Trust, Trust, Trust

Now that you are building your connections, you need to ensure you maintain trust. Many people avoid the forecasting process because it is one where you are often wrong. Make sure you give lots of credit to your colleague/s in Sales when you get information that leads to a better forecast.

You also need to show appreciation for the effort in getting information that may not be valuable as well. Customers are not always forthcoming with their numbers but having a Salesperson that is willing to make the effort and engage with a customer to get information is extremely valuable. As you develop a good flow of customer information, you can utilize and learn to refine the data over time.

Remind Salespeople frequently why good forecasts are important. If your motivation is about better customer service and improving profitability, you will get more support than if your only motivation is to improve your own MAPE.

Think Like A Salesperson

Sometimes you need to act like you are in Sales to communicate with Sales. Anyone who has worked in Sales knows you need to be persistent to get a customer’s business. You may have to be persistent to get their responses and to hold their interest. Do not give up when you don’t get fast responses to your questions. Instead, keep asking how you can help them serve our customers better. Remember, persistence pays off.

As you review data, you can also think like salespeople. For example, I noticed that one of our customer’s volumes had declined over the years on a group of items. Since the Salesperson in charge of this account was new, this information provided him a previously unknown opportunity to pursue. Often customers are moved between members of the Sales team, and information is not always transferred effectively.

Do not assume that important pieces of information like this are already known. By providing helpful insights to new hires, you will build better relationships.

When reviewing future sales projections, most salespeople tend to be optimists. To help reduce this spin, I often ask them to project as if they were wagering their own money on the outcome. Phrasing the question to include a pretend bet on the outcome, using money out of their own pocket, may change their frame of mind to be more realistic.

Sell them on ideas like participating in annual sales planning meetings, getting you access to customer portals, including you in customer calls, and even connecting you to individuals at the customer who are directly involved in the purchasing process. If you can take some of the burden off Sales and get information directly, you both win.

When hiring Demand Planners, consider those with successful experiences in selling or working with Sales as they can bring valuable skills to your team. Sometimes it helps to think small if you have just begun to work with the Sales team. Start by building a strong relationship with just one member of the Sales team, and that can become a springboard to expanding your reach. Showing others the work you have done with another member of their team is an effective way to expand your network with the Sales team.

Keep Score & Take Advantage Of Salespeoples’ Competitive Nature

You need to introduce forecast metrics into the conversation at some point, but keep it simple, especially in the beginning. Forget about MAPE, WMAPE, MAD and other metrics that are difficult to understand and not directly relevant to salespeople. For example, try forecast bias percentage (forecast/shipments-1).

This measure is an easy way to show trends in forecast performance that need attention. If you are showing your sales partner that we have over forecasted their customer by 25% the last 4 months, this is a good starting point to take action, and does not require a background in statistics.

Connect metrics directly to each salesperson through their customer and establish forecasting metric targets that are adjusted to the variability of the customer. The most challenging customers should have lower forecast accuracy targets, and vice versa. Your goal is to create a level playing field to stoke competitiveness among your selling professionals. At virtual meetings with the entire sales team present, I have had a lot of fun presenting a Forecaster of the Month award, complete with certificate and photo. Make sure they understand how the metric works, how they can provide additional insights to potentially override the current model, and let the games begin!

Keep It Simple

Everyone’s time is valuable. As I mentioned above, keep metrics easy to understand, and keep the data you share simple, and in a format where it is easy to see the key points. During your forecast discussions or exchanges with your Sales partner, don’t ask for analysis, instead ask for answers. Lay out the situation, then provide specific options or directions to take.

My questions look more like multiple choice rather than ‘fill in the blanks’. I have found this approach to return clear and actionable responses. If you are not getting actionable responses, you may need to better frame how you are asking the question.

Ultimately, where Sales can lend the most value in planning is to explain or — better yet, alert to — outliers. Statistical models do fine when demand is steady while qualitative customer information is very valuable is when there is a change in course. Did a customer gain new volume and, if so, approximately how much and when will it begin? Has there been a shut down due to the pandemic, did they delay a new product launch, or even go out of business?

Since you are now like a member of their team, and better understand their business, you can ask simple, clear and relevant questions and get valuable insight that explains outliers and improves your forecasts.

Win Over Their Leader

As with any large and important change initiative, you need to get their leader’s support early. You may have to work hard to convince them to adopt a forecast KPI to their metrics—to facilitate this, share the dollar value of improving forecast accuracy, i.e., what savings are gained for every one percent improvement in under- or over-forecasting.

If you have not done this exercise, IBF has easy-to-use calculators that can help. Connecting dollars to forecasting improvement will help you get your Sales Leader interested. Remember, how their leader interacts with the demand planning team will set the tone for how the Sales team as a whole interacts with you.

Remember that effective relationships are built over time, not overnight. This is especially true if Sales and Demand Planning have not had a strong connection in the past. By applying the tips above, being an engaged partner, and being willing to lend a hand when needed, you will gain insights into your customers’ behavior and intelligence that will lead to better qualitative forecast inputs.

This article originally appeared in the Spring 2021 issue of The Journal of Business Forecasting. Become an IBF member and get the Journal delivered to your door quarterly, plus discounted entry to IBF conferences and events, members only tutorials and workshops, access to the entire IBF knowledge library and more. Get your membership. 

A few years back we decided to totally change the way we created forecasts and did something radical – we fired Sales from generating the monthly forecast. The result was more collaboration, less time creating plans, and improved forecast accuracy. The best part? Sales, Supply Chain, and myself were much happier as a result.

The more time I spend in this field, the more I believe Sales should not be forecasting. For starters, we all agree it is not the best use of their time. Secondly, let’s face it, they are not that good at forecasting either. As a Demand Planner now, I personally do not want sales to forecast every customer and item every month – just give me the Cliff notes.

This may not seem radical to some but for us it was a big change. Forecasts had been created by our Sales team since forever and were aggregated up to create plans. It made sense when they started; they were closest to the customer and they were accountable for converting leads to revenue. They knew what was broadly possible in terms of sales so it kind of made sense.

Salespeople Are Not Good Forecasters

The problem, however, is that this process would take a good week or more every month. They needed a long time to generate the forecast, aggregate data, review the top lines, and see if they were hitting plans. The even bigger issue was that while they were close to the customer and had a feeling for what is occurring this month, our forecast needed to be 3 months out so supply chain had enough time to ensure enough product was ready to fulfil demand. When it came to forecasting out 3 months, Sales were, for the most part, simply guessing. They were creating “wish-casts” and not a forecast.

There’s A Better Way To Forecast

When I say Sales are not good forecasters, I am allowed to say that because I grew up on the commercial side of the business. I was a Marketing and Sales analyst who was in charge of aggregating those forecasts and delivering the final plan. Following a move into Supply Chain and having done IBF training and my own studying to really understand demand planning, I found a better way:

• Start with a statistical baseline
• Let Sales know what kind of information you need
• Build a structured process for inputs and review
• Adjust the forecast for what it doesn’t know
• Drive a consensus forecast
• Measure the process and FVA%

Our new way of creating a forecast began with an automated statistical forecast as our baseline. It was my job then to add in outside variables like promotions and other factors. The forecast was then disaggregated and created for each salesperson to add specialized market intelligence and be ready to discuss if there were questions.

Now, on the first Thursday of every period, we have our demand review and we add anything that was not in the plan and finalize a consensus forecast. There are always some additional ad hoc calls and emails prior to the demand review to clarify details on some aspects.

What Happened When We Took Over The Forecast Process?

The end result was that Sales avoided spending countless hours dealing with numbers and trying to create forecasts without the requisite skills. It meant less time spent in meetings and on a computer. It freed up time for them to what they do best: prospecting, selling, and closing.

When I said that Sales shouldn’t be forecasting, that doesn’t mean we don’t want their input. Using a statistical baseline as our starting point, we already know things like level, trends, and seasonality. We know that the biggest selling season happens every summer and that demand on holidays repeats. But there are things we need to know that are not baked into the baseline forecast. Like Patrick Bower said in the comments of one of my recent LinkedIn posts, “ask Sales for more structured data. i.e., new customers, new distribution, new promotions, deletions etc.”

A concern when transitioning to this new process was that Sales would no longer have accountability and we would get less participation and less of the information we need. What we discovered was that a consensus forecast actually drives group accountability and ownership. Collaboration increased with a structured approach that helped them in the long run. As forecasts improved, service improved which facilitated their sales efforts.

One more thing – last year I added a new key performance indicator, Forecast Value Added (FVA) after it was highlighted in one of Eric Wilson’s podcasts (The Magic of Forecast Value Added). This KPI allowed Sales to understand how their input into the process impacted forecast accuracy which fostered more accountability and drove more collaboration.

For more insight into forecasting and planning best practices, join us at IBF’s Business Forecasting, Planning & S&OP Conference in Orlando, held from October 19-22 at the Wyndham Orlando Resort. The biggest and best event of it’s kind, it’s your opportunity to learn best practices in S&OP, demand planning and forecasting, and network and socialize in a fantastic setting. See here for details.

I have never seen two demand planners working in the same way. Sometimes I am really surprised how different the same role can be in different organizations – or even within the same organization. There’s one universal truth, however: that interaction with sales teams is challenging, and getting the most out of them requires a well-thought out plan.

The worst-case scenario I can imagine for a Demand Planner is where they are limited to the role of “stock provider” who merely takes figures from Sales and maintains the system. The best-case scenario is when a real partnership is built with Sales teams where they provide not only quality inputs for forecasts, but collaborate with Demand Planners about how to best quantify their input.

Sales Are Not The Enemy

A stereotype outside of Supply Chain is that Demand Planners have the wrong priorities, like focusing on forecast accuracy metrics instead of fulfilling customer orders. I think that all Demand Planners agree that they’ll be in much bigger trouble when there’s insufficient stock to fulfill customer orders than failing to meet accuracy targets. But it is up to us as Demand Planners to communicate how things like forecast accuracy metrics help ensure there’s sufficient stock to fulfill customer orders. A lack of understanding and transparency about what we do erodes confidence in the forecasting process, and can lead to a situation where agreement on final numbers is driven by silo-based interests instead of fact-based analysis. The work of Sales teams and Demand Planners should be complementary, not competitive – and that means being transparent about what is it you’re doing and how it serves the aims of Sales.

Here I share two scenarios of cooperation with Commercial teams, one ineffective and one effective.

How To Ineffectively Work With Sales Teams

Coming to the meeting with pre-defined numbers from both sides is not the best idea. Why is that? Firstly, because two teams are doing the same work, and it is a waste of time for two functions to do the same thing when it can be dome by one.

Secondly, a competitive approach to the numbers is pointless – it does not help the company gain an accurate view of future demand. What’s more, the Sales team is likely to win this pointless game every time for one simple reason: asymmetry of information. Both Demand Planning and Sales have the same historical data but Sales has the advantage of knowing upcoming events that will impact sales orders. By events I mean activities that will not only boost sales like promotions but also other factors that can negatively impact demand (lack of repeatable promotion, loss of distribution, price increases etc.).

At this point we need to ask an important question: Should Sales teams actually be involved in forecasting at all? Let’s move to the second scenario where I will provide the answer to this question.

How To Effectively Work With Sales Teams

Sales should focus on selling, not forecasting. But they do need to be part of the S&OP process. There are 3 major areas where they need to add value to the S&OP process: providing unbiased, quality information; consulting on final figures for the forecast; and providing input to post-validation of forecast accuracy.

I will expand on each of these points:

Providing unbiased quality information: An example here would be promotions by a customer (type of promo and when). The action for the Demand Planner would be to find in historical data what kind of uplift was generated by similar promotions by this customer in the past, and combining it with statistical forecasts for the remaining customers to arrive at a total figure for whole market. The above discussion between teams can happen at the first demand review meeting whose aim is to gather assumptions to prepare the forecast. Methods for including the promo uplift data into the statistical forecast is a topic for very long debate, and I will not go into details in this article.

Consulting on final figures: Once the Demand Planner prepares the forecast based on a combination of statistics and the estimated promo uplift, Sales should tell us if these figures makes sense. If not, what assumptions should be changed or estimated differently? Is the statistical trend wrong? Should promo volumes be projected differently? This discussion ideally takes place at the second demand review meeting before reaching consensus and presenting the forecast to upper management. The level of discussion is not SKU level, but rather product group or another aggregation level that makes sense depending on the business.

Input to post-validation of accuracy results: Updating the plan/forecast is only one side of the coin, similar attention should be paid to post-validation of forecast accuracy and finding the root causes of errors. Here Sales plays a major role as they have access to all market knowledge that helps to interpret actual sales data. An example here is ad-hoc promotion initiated by customers which explains a sales peak that was not accounted for in the forecast. The role of demand planner is to keep track of circumstances that can explain data anomalies.

There are 3 benefits to be gained from proper documentation of forecast error root causes. Firstly, it gives us information to be used in future (like overly-optimistic assumptions for promo sales or new products). Secondly, this information helps us to clean sales history or decide about adjustments to forecasts for corresponding months next year. Thirdly, it means we have documented knowledge that we can pass on to the new Demand Planner when the current one leaves the company or changes his/her role.

The above points can be summarized by below graphic:Summary

Sales’ engagement is critical for a successful forecasting process and, subsequently, a successful S&OP/IBP process. One question that remains is what their actual role should be in the process. Should it be preparing their own high-level estimations or focusing on providing reliable information? I am signing up for the latter. Obviously, information provided by Sales will always carry some degree of uncertainty as customers can change their mind at the last moment.

Sales teams should not hesitate to give their opinions, and be prepared to consult on, and sign off on, the official figures. However, they should not spend time on preparing their own estimations as this is the Demand Planner’s responsibility and area of expertise. Although it takes time to break silos and build trust between functions, the above efforts can deliver better forecast accuracy and better control of planning.

The Institute Of Business Forecasting (IBF) defines S&OP as “process that integrates demand, supply, and financial planning into one game plan for business.” It also “links strategic plans to operational plans, and attempts to develop the most desirable product portfolio and product mix to maximize sales and profit.”

The Challenge

Call it by any name. S&OP, SIOP, IBP or IBM, the basic framework remains the same. And S&OP, instead of being an end to end business capability, has evolved into purely a supply chain capability. After 30 + years of S&OP we still don’t see the involvement of Sales people in the S&OP process in most organizations. They are reluctant participants at best, and are not seen at any S&OP seminars or conferences, nor will you see them writing blogs or posts on LinkedIn groups. This lack of engagement is what is holding back S&OP from its full potential.

Has anybody seen the Sales department?

The Real World

Most organizations start S&OP from a purely operational perspective. It is mostly initiated by the head of Operations. In fact, if you go back to the roots of S&OP, it was created to be a process that led the master schedule. Studies have shown that in most S&OP implementations, the process owners are typically heads of supply chain.

I once had the good fortune of having two sales managers attend a presentation I made at an S&OP conference. I started the session by asking the audience how many were from the Sales & Marketing side of the business and, being sure that nobody was going to raise their hand, this was my way of showing that Sales were missing from the S&OP process. To my surprise, I had 2 hands go up. I requested them to stand up and asked the audience to give them a big round of applause. This was a rare sight and something to be cherished.

I do not see Sales people coming to S&OP conferences if we are going to be talking about and showing off our technical systems and processes.

The two sessions after mine were on Artificial Intelligence and Demand Driven forecasting – very technical content totally focusing on the Tools and capabilities to improve demand forecasting. Guess what happened when we returned after lunch? The two Sales guys have gone missing. We scared them away by talking about complicated new fangled technology that had nothing to do with their jobs or objectives.

If we cannot get Sales involved, we may as well remove the “S” from S&OP and add it to our supply chain processes.

I do not see sales people coming to S&OP conferences if we are going to be talking about, and showing off, our technical systems and processes. S&OP is a great process but it continues to suffer from being a supply chain focused process. If we cannot get Sales involved, we may as well remove the “S” from S&OP and call it by any other name and add it to our supply chain processes.

Four Pillars to build the S&OP Process

To successfully build the S&OP process with the full commitment of the Sales and Marketing team, it is important that we address these four areas. These help deliver a collaborative process that benefits every department.

Top Management Support

The most important thing about S&OP is bringing Sales and Operations together in charting the future of the company and this can be done only by the person to whom both report. Without the commitment of the most senior executive, the S&OP process will fail. It is important to ensure that all meeting requests are sent out well in advance and all S&OP Executive Meetings are chaired by the CEO.

The beauty of S&OP are the soft benefits which come early on. Sell soft benefits to the CEO and he will be all ears, this gets him motivated and keeps him engaged. When results appear, he’ll wants to attend all Executive meetings.

Consistency & Discipline

Consistency in meetings and discipline are the framework of a robust S&OP process. Consistency is the difference between failure and success as it enables measurement, creates accountability and reinforces the message.

Fixed agendas for the meeting communicated well in advance facilitate the discipline required for these meetings. Without a fixed agenda and discipline, the meetings will soon be unproductive – people wander off topic and participants spend more time digressing than discussing. Stick to the agenda!

Transparency In Data sharing & Agile Decision Making

Transparency in  S&OP data, measurement metrics and the feedback loop enables higher trust levels among participants.

In S&OP meetings, success is often determined by the ability to be quick on your feet and react to changing scenarios. It is very critical that each person in the S&OP meeting has the authority and is empowered to take decisions when required.

Follow-up actions from every meeting need to be properly documented and communicated to all stakeholders

Once the Demand Forecast is agreed on by S&OP stakeholders, any discussions on forecast accuracy should be on what WE got right, what did WE miss, and how do WE improve the process. The discussion should not be on what the demand team forecasted and placing blame.

Trust

S&OP is a collaborative process. Collaboration happens when participants trust eachother. An open, trusting attitude is a must for success. Every participant must believe that they all share a common goal, and everyone else is doing their best for the common success of the team.

In most companies, the S&OP leader is either from the Sales or the Operations team. The biggest boost to trust levels can be brought about by having the S&OP leader report to the CEO.

Salespeople are key players in an effective demand planning process. They can provide timely input on their customer’s plans and issues from the front line. They hear the voice of the customer first. However, gaining their confidence is challenging, especially if they don’t understand our role in the planning process. As Demand Planners. we need to proactively build strong relationships with our sales teams so they freely share their customer knowledge with us.

To accomplish this, here are 5 practices I have used to build good relationships with sales people:

1. Understand the salesperson’s world.
2. Provide data to help them understand their customer’s business
3. Help them understand the corporate and S&OP expectations for their program
4. Help them deal with difficult customers and service outages
5. Warn them when difficult conversations may be necessary

1 – Understand The Salesperson’s World

Most salespeople operate outside of a corporate environment and often the relationship with the corporate office is strained. The daily challenges they face and the pressure they are under are often very different from what their counterparts in the corporate office face. Difficult customers, traffic, poor service, defective products and missed deliveries are frequently on their list of daily issues. So if we are going to ask these sales people to work with us and trust us, we will need to start building our relationship with them by understanding how they spend their time, and the problems they need to solve.

In my experience, this means arranging a time to call them when they have time to really explain and teach us about how they get their work done, and what gets in the way of their performance. It also means scheduling time to regularly check in with them throughout the year and really listening to them. They need to feel that we both care about, and want to understand, their world and what it takes to succeed there.

2 – Provide Data To Help Them Understand Their Customer’s Business

In my experience, salespeople crave useful data. They often don’t have time to compile it themselves, and they rarely have time to digest large amounts of it. So, the more we can provide them with focused data – data that tells them about the health of their customer’s business, and where there is opportunity or risk – the more we will be seen as allies in the sales process. And if we can do this via graphical data – charts, graphs, summaries – rather than long numeric reports – the more likely they will appreciate and use the data. When in doubt, ask them what data they would like to see, how often they want it, and what format would best serve them. And be prepared to tailor the data to each individual salesperson.

3 – Help Them Understand And Manage The Corporate And S&OP Expectations For Their Program

Sales people get paid to make their plan numbers. Often their plan targets are challenging, and sometimes they are truly unrealistic based on what is happening with their customers. While we as Demand Planners cannot take sides in these cases, we can coach the salespeople on strategies that can help them. We can help them teach the customer about what is happening in the overall market by sharing data with the salesperson on item performance with similar customers. We can offer marketing expertise to help the salesperson move the customer out of old products and into new a more appropriate SKUs, or show them what items or promotions were effective in the past. And we can show them how to speak to the opportunities and risks in their business in language that both the corporation and the S&OP teams will understand.

4 – Help Them Deal With Difficult Customers And Service Outages

Nothing is more frustrating to a salesperson than dealing with a difficult but profitable customer. Customers who demand special services, ask for special discounts or who consistently wants additional attention can quickly wear down even the most energetic salesperson. So if we can provide reporting to help solve these issues, get our supply team involved in providing updates on missing or damaged shipments, or get finance to help with pricing and discount questions, this will go a long way toward building the salesperson’s trust and confidence in us. In my own career I have even called customers to apologize for service outages so that the salesperson could maintain a positive relationship with the customer.

5 – Warn Them When Difficult Conversations May Be Necessary

When business is not good and sales are lagging, the pressure on the sales teams can be enormous. They know when they are missing their plan numbers. What they often don’t know is how to frame the conversations around their plan misses, and when these hard conversations may occur. As Demand Planners we can see when a salesperson is missing their plan. We often know what is causing the miss, and hopefully we have communicated this to them and provided them with reporting to back up our conclusions. And as Demand Planners we are often aware of how the company sees the lagging performance, and we can tactfully coach the salespeople on how to explain what is happening that is holding their performance back.

Building good relationships with our sales teams can give us a significant advantage in our planning efforts. Our salespeople can warn us about customers that are not performing as expected, and can give us a chance to manage our forecasts to account for this. As Demand Planners we want the salespeople to be our allies. At the same time we also need to teach them that while we will not hide poor performance, we will do what we can to help them reach their goals and provide outstanding service to their customers.

They need to know that we want them to succeed, so that when they meet with their customers they can be confident that they programs they are presenting are realistic and truly support the customer’s business.

If you have any knowledge of Demand Planning, I am sure that you have heard the following: “Demand Planners are like meteorologists, they rarely get credit for doing the job correctly and they’re only noticed when they get it wrong.” Even so, the bottom line is that there are serious and costly ramifications which can occur if these decisions are wrong. For this reason, the demand planning position can be one of the most important and visible in the company. It is a great place to impact many areas of business and gain corporate approval. It is best to take a positive approach and be an agent for fact based decision making. Using this approach, along with good communication skills, is a great avenue to gain the knowledge and build relationships that will prepare you for success and lead you along a career path with much variety.

Demand Planning is Transferable To Any Industry

Demand Planning touches every aspect of the business and the impact can make this person a valuable asset very quickly. It requires broad business knowledge and detailed customer interaction. Also, it is a functional area that has the ability to transfer these skills to any industry. It involves working with several areas of the business simultaneously and provides an excellent opportunity to tap into the  knowledge of others. Also, working in cross functional teams can be very rewarding by providing a lot of variability to the job and making it more pleasurable.
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Demand Planning Is A Collaborative Process That Provides Visibility, And Opens Doors

It is a collaborative process which aids in developing many relationships through the internal organization, as well as, customers and other suppliers. It is a highly visible position which can lead to new and exciting projects. Along with the knowledge to be gained from these groups, the relationships become an asset for your forecasting success and in turn your career path. Also, it can be very rewarding to work with other people to help them attain their goals and reach a collaborative decision that will benefit the entire company. A successful demand planner must become a leader in fact based decision making and a champion for change.

The Required Leadership In The Role Is a Challenge

Along with business knowledge and relationship building, leadership skills are also an asset to a successful demand planner. A successful demand planner uses the knowledge gained and is able to interact with customers, managers, sales representative, marketing, pricing and supply chain colleagues. Becoming a good communicator is imperative to collaboration among internal and external customers. This will enable the demand planner to guide various groups in terms that make sense to them and to reach consensus among the group. All of these things together help the demand planner to provide the best forecast possible which in turn will become a huge advantage for both the company and the demand planner.

Ultimately, a bad forecast leads to bad corporate decisions and the loss of career possibilities. Take the positive approach using business knowledge, building relationships and leading your colleagues to collaboration. Pave the way for fact based decisions that will benefit you and your company. Don’t become a victim and fall for the curse. I have learned over the years to approach my career and my life with gratitude and a “can I help you” attitude. This will take you farther than any expertise on any day. Curse or Blessing, well maybe it was best defined by the Beatles, “I get by with a little help from my friends.”

Sylvia Starnes
Demand Planning Leader
Continental Tire

Globalization has intensified competition. Every day, thousands and thousands of new products enter the market, but their window of opportunity is very narrow because of shorter life cycles. Plus, too much uncertainty is associated with new products. Their success rate is from poor to dismal—25% according to one estimate. Despite that, they are vital for fueling growth. Big box retailers are putting more pressure on suppliers to provide differentiated products. Consumers want more choices and better products. All these factors contribute to the greater than ever number of products and product lines, making management of their demand more complex, increasing working capital to maintain safety stock, raising liability of slow-moving and obsolete inventory, and increasing cost of production because of smaller lots and frequent change overs. Product portfolio optimization deals with these matters.

Product portfolio optimization includes the following: one, how to rationalize products and product lines and, two, how to manage most effectively their demand. Product rationalization includes deciding which products and product lines to keep and which ones to kill, based on the company’s policy. Demand management, on the other hand, is leveraging what Larry Lapide from University of Massachusetts and an MIT Research affiliate calls 4Ps (Product, Promotion, Price, and Place) to maximize sales and pro‑t. The sales of low-performing product lines may be bumped up with a price discount, promotion, line extensions, or by finding new markets.

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Although the S&OP process has a component of product portfolio optimization, its team members pay nothing more than lip service to it. Pat Bower from Combe Incorporated discusses in detail the process of product portfolio optimization in the framework of new products. How new products should be filtered from ideation to development and, after launch, how they should be leveraged. Their window of opportunity is very small; most CPG products flame out within the first year of their existence, says Pat.

Mark Covas from Coca-Cola describes in detail 10 rules for product portfolio optimization. He suggests companies should divest low margin brands, no matter how big they are. Many companies such as ConAgra Foods, General Mills, Procter & Gamble, and Estée Lauder are doing it. This makes the allocation of marketing dollars more productive—taking funds away from low performing brands and giving to high performing ones.

Charles Chase from SAS and Michael Moore from DuPont recommend the Pareto principle of 80/20 to determine which products or product lines to concentrate on in their portfolio optimization e­fforts. Greg Schlegel from SherTrack LLC. Goes even further and proposes that this principle should be extended even to customers. He categorizes customers into four: 1) Champions, 2) Demanders, 3) Acquaintances, and 4) Losers. He then describes a strategy for dealing with each one of them. Greg Gorbos from BASF points out hurdles, political and others, that stand in the way of implementing the optimization policy, and how to deal with them. Clash occurs among different functions because of difference in their objectives. Sales looks to achieve revenue targets, while Marketing looks to hold market share and increase profit. Finance also looks at profit, but seeks to reduce cost and increase capital flow, while Supply Chain looks at cost savings. Communication is another issue Greg points out. The company may decide to deactivate a product, but information about it is not communicated to all the functions. Je­ff Marthins from Tastykake talks, among other things, about the exit strategy, which he believes is equally important. He says that we cannot deactivate a product without knowing its inventory position, as well as holding of raw and packaging materials for it.

For survival and growth in today’s atmosphere, it is essential to streamline the product portfolio to reduce costs, and increase revenue, profit, and market share. This issue shows how.

I encourage you to email your feedback on this issue, as well as on ideas and suggested topics for future JBF special issues and articles.

Happy Forecasting!

Chaman L. Jain
Chief Editor, Journal of Business Forecasting (JBF)
Professor, St. John’s University
EMAIL:  jainc [at] stjohns.edu

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While I don’t obsessively worry about every possible risk, I am aware of the possibilities and I take measures to lower both the odds and severity of a mishap. I keep my vehicle well maintained, I buckle up and I pay my auto insurance. Similarly, today’s supply chain professionals must be more conscientious and proactive in their efforts to mitigate the risk of a supply chain disruption and to minimize the impact when the inevitable does occur.

As much as we may feel at the mercy of disruptions from severe weather, natural disasters, economic instability or political and social unrest, members of today’s high tech supply chain have never been better equipped to minimize the risks and capitalize on the opportunities that may arise from a supply chain disturbance.

One of the most simple, but powerful, tools at our disposal is information. Twenty-four hour news stations, social media and cellular communications give us literally instant access to events occurring in the most remote reaches of the world.

More tactically, mapping the physical network of the supply base, including manufacturing facilities, warehouses and distribution hubs, is an important part of any risk management strategy. The key here is mapping the entire supply chain network, not just top-spend suppliers or first-tier contract manufacturers. Most of this information is relatively accessible through supplier audits and, with the help of Google maps, you can create a pretty comprehensive picture of your physical supply chain.

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Remember, though, supply chains are much more fluid than they have ever been. Today’s multinationals are likely to rely on three to five different contract manufacturers (CMs) and original design manufacturers (ODMs), and scores of other suppliers around the world for the tens of thousands of parts needed to build and maintain their products. With outsourced production so commonplace, production lines can be shifted between locations within a matter of weeks, so frequent monitoring and updating of supply chain shifts is critical.

IoT technology such as sensors and RFID tracking can also provide meaningful intelligence that may be used to identify and mitigate risk throughout the end-to-end supply chain process. The ability to gather and analyze these constant data inputs is a recognized challenge throughout the supply chain profession. Those who master the digital supply chain sooner, will enjoy a substantial competitive advantage.

Once these various vehicles are used to create a composite picture of the risk landscape, then risk mitigation strategies take center stage. These efforts can range from traditional techniques such as the assignment of a cache of safety stock to more intricate maneuvering of storage facilities and full network design. Deployment of these mitigation strategies requires a detailed recovery and communications plan.

In my upcoming presentation at IBF’s Supply Chain Forecasting & Planning Conference at the DoubleTree Resort by Hilton in Scottsdale, AZ, February 22-23, 2016, I will delve deeper into the growing range of potential disruptors in the high tech supply chain. I will outline the core elements of a comprehensive supply chain risk management strategy, including how to define and map the physical supply chain, the landscape around supply chain risks and their impact on financial metrics, and how to proactively assess potential risk. I hope to see you there.

Forecast Error

The first session I attended on Tuesday was “How to Measure & Reduce Error, and the Cost of Being Wrong” an advanced session presented by Dr. Chaman Jain from St. John’s University.  Dr. Jain reviewed the basic methods and mechanics of how to compute forecast error and the pros and cons of each technique. It was interesting that IBF has found that more and more companies are moving from MAPE (Mean Absolute Percentage Error) to a Weighted MAPE (WMAPE) to focus their attention on errors that have a relatively larger impact or little to no impact at all.  Standard MAPE treats all errors “equally”, while WMAPE places greater significance on errors associated with the “larger” items. The weighting mechanism can vary, typically unit sales are used, but I was intrigued by the notion of using sales revenue and profit margin as well.  If a company has low volume items but they are big revenue and profit items, they would not want to miss an opportunity to focus attention on why they have significant errors on these items.

Another interesting concept that Dr. Jain discussed was the use of confidence intervals around error measurements.  Many companies report their error measurement as a single number and rarely present the error measure in terms of a range of potential errors that are likely. Having a view into the potential range of errors can allow firms to exercise scenario planning to understand the impact to supply chain operations and the associated sales based upon multiple forecast errors instead of a single number.

My last takeaway is related to the question of how much history should be used to support time series analysis. Dr. Jain stated, and I believe rightly so, that it depends. Are there potential seasonality, trend, business cycles, or one-time events? How much does one need to see these? What if the past is really not a good indicator anymore of the future? What if the drivers of demand for a product have substantially shifted? One technique suggested that seems sound is to test the forecasting model’s performance using different periods of historical data. Use a portion of the history to build the model, and the remaining portion to test the accuracy of the forecast against the actuals held out of model construction. Try different lengths until you find the one that has the lowest error and also allow the process to have different history lengths for each time series forecast.

Lean Forecasting & Planning

Next I attended another advanced session led by Jeff Marthins from Tasty Baking Company/Flowers Foods on “Lean Forecasting & Planning: Preparing Forecasts Faster with Less Resources”. The session focused on doing more with less, a common theme that has permeated the business world these last several years. Marthins’ session was really about how to focus on what matters in demand planning: looking at the overall process, agreeing to and sticking with the various roles and responsibilities in the process, and understanding how the resulting forecasts and plans are to be used by various consumers in the business which drives the level of detail, accuracy and frequency of updates.

To gain an understanding of the demand planning process, Marthins asked the participants to look at a picture of his refrigerator and answer “Do I have enough milk?” This relatively simple, fun question elicited numerous inquiries from the participants around consumption patterns, replenishment policies and practices, sourcing rules, supplier capacity and financial constraints that illustrated the various types and sources of information that are required to develop a solid, well-thought-out demand plan. It was a very effective approach that can be applied to any product in any company.

To illustrate the need to understand the level of accuracy required of a forecast, Marthins used the weather forecast. How accurate is the weather forecast? How often is it right? How precise does it need to be? Once we know the temperate is going to be above 90 degrees fahrenheit, does it matter if is 91 or 94 degrees?  Is there a big difference between at 70% chance of rain or an 85% chance of rain?  What will you do differently in these situations with a more precise weather forecast? Should I plan to grill tonight? Will I need to wear a sweater this evening? Can we go swimming?  If the answer is nothing, then the precision does not really matter and spending time and effort creating or searching for greater forecast accuracy is a “waste” and wastes should be eliminated or reduced in Lean thinking. Marthins also stressed the value of designing your demand planning process with the usage of information in mind. Adopting a Forecast Value Add (FVA) mentality to assess whether each step in your forecasting and demand planning process is adding value will help to accomplish this. Start by asking if the first step in your forecasting process results in greater accuracy than a naïve forecast such as using the same number as last time you forecasted, or a simple moving average? When your accuracy improves with each step in the process, is it worth the effort or time it takes? Can I be less accurate and more responsive and still not have a negative impact? If I can update my forecast every day with 90% accuracy versus once a week with 92% accuracy, or once a month with 96%, which is better? How responsive can I be to the market by making daily adjustments that are nearly as accurate as weekly ones?

In yet another session, the topic of scenario analysis was raised. The team at IBF are getting this one right making sure it is discussed in multiple sessions. What I wonder is how many companies are adopting scenario analysis in the demand planning and S&OP processes? From my experience it is not the norm.  Marthins suggested testing the impact of various forecasts, and hence forecast accuracies, would have on supply chain performance and even using scenario analysis to understand if a systematic bias, either high or low, might make sense. I have known companies that have employed the policy of allowing overestimating to ensure their resulting demand plan was on the high side. Carrying more inventory even with all the associated costs was of greater benefit to the company than a lost sale or backorder. Bias is not a bad thing if you understand how it is used and its resulting impact, just like inventory is not an evil when used in a planned and methodical manner.
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Data Cleansing

After lunch I attended my second session delivered by Mark Lawless from IBF “Data Cleansing: How to Select, Clean, and Manage Data for Greater Forecasting Performance”. As in any analytical process, the quality of the inputs are crucial to delivering quality results. Unfortunately I had another commitment during the session and I could not stay for all of it.

Lawless discussed a variety of ways to look at the data available, decide if it should be used, update or modify it, fill in missing values and apply various forecasting techniques.  Simple reminders and tips such as consideration and awareness for how data is provided in time periods, e.g., fiscal months (4/4/5) or calendar months, and how they should be reported was a good reminder to make sure the data inputs are clearly understood as well as how the output from the forecasting process will be used.

While most of what I heard was related to the data going into the forecasting process, Lawless did spend time talking about various analytics associated with assessing the output of the process. You might be expecting me to talk about various error and bias metrics again but that is not the case. Rather, the idea is to look at the error measurement over time.  What is the distribution of errors? Do they have a pattern or random? If there is a pattern, there is likely something “wrong” with the forecasting process. It made me think about the application of Statistical Process Control (SPC) techniques that are most often applied to manufacturing processes but can be applied to any process. SPC control charts can be applied to check for patterns such as trends, systematic sustained increases, extend periods of time at unexpected very high or very low errors, randomness of errors, and many more. It gets back to the notion that in order to improve the quality of the demand planning process it must be evaluated on a regular basis and causes for its underperformance understood and corrected as much as possible or warranted.

Regression Analysis/ Causal Modeling

The final advanced session of the Academy was delivered by Charles Chase from the SAS Institute on “Analytics for Predicting Sales on Promotional Activities, Events, Demand Signals, and More”.  This session was about regression modeling on steroids.  As someone who has used regression models throughout my career I could easily relate to and appreciate what Chase was discussing.  In two hours Chase did a great job exposing attendees to the concepts, proper use, and mechanics of multivariate regression modeling that would typically be taught as an entire course over weeks.

While time series models are a staple used to forecast future demand, they provide little to no understanding of what can be done to influence the demand to be higher or lower. They can be used to decompose the demand into components such as trend, seasonality and cycles which are important to understand and respond to.  They are focused on the “accuracy” of the predicted future.  Regression models however describe how inputs effect output. They are an excellent tool for shaping demand. Regression models can help us understand the effect internal factors such as price, promotional activity, and lead-times, as well as external factors such as weather, currency fluctuations, and inflation rates have on demand. The more we can create predictive models of demand based on internal factors the more we can influence the resulting demand as these factors are ones we control/influence as a firm. If external factors are included, forecasts for the future values of these inputs will be needed and we become more reliant on the accuracy of the input forecasts to drive our model demand.

In case you missed it, you can see pictures from the 2015 IBF Academy HERE.

I trust I have brought some insight into IBF’s recent Academy in Las Vegas and perhaps offered a nugget or two for you to improve your forecasting and demand planning activities. If only I would have learned something to apply forecasting success at the gaming tables :).

The key question becomes what do we do with all this data? In the past, companies have always struggled with managing and analyzing large sets of data and could seldom generate any insights.

However, what’s different today vis-à-vis five years ago, is that we now have the ability to cleanse, transform and analyze this data to generate actionable insights. Moreover, today’s retail consumers are extremely demanding and want choices on “When”, “Where” and “How” to purchase product. Whether it is a traditional stand-alone retail store, shop-in-shop, website or mobile app; consumers want the flexibility to research, purchase and return product across multiple channels.

Today, many retailers and wholesalers have a vast amount of POS data available. However, many of them still don’t use the data at the lowest level of detail in their demand planning cycle. The result is significant out of stocks and inability of consumer to find product at the stores.

For a company to be successful in today’s Omni-channel environment, three key steps are needed:

1) Use Point-of-Sale (POS) data as a key input into demand plans: POS is the data that is closest to the consumer and is the purest form of demand- it is critical to leverage this data at the right level of detail into a product’s demand plans. Information available at stock-keeping-unit (SKU) level- should be aggregated and disaggregated to ensure that all attributes of a product are factored into the planned forecast.
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2) Link Point-of-Sale (POS) data to your Allocation & Inventory Management Systems: Today’s allocation systems have the ability to read sell-thru at POS and react and replenish based on what product is selling and what is not. It is critical to make sure that these systems are linked together so that the process is automated and seamless. Linking these systems will allow retailers to send the right product to the right store at the right time- thereby maximizing the chances of making a sale. This will not only contribute to top-line, but will also make our inventory investments more productive.

3) Collaboration with Value Chain Partners to share Point-of-Sale (POS) data: Today’s retail world is complex, many companies have multi-channel operations and work with a number of channel partners to distribute their products. In such a scenario, it is not always easy to gain access to POS data. However, it is important for companies to invest in a CPFR program (Collaborative Planning, Forecasting and Replenishment) that can give them access to downstream POS data which can be used to build better forecasts. It is critical to emphasize a “Win-Win” relationship for both companies and channel partners to bring everyone along on the collaboration journey

Along with Rene Saroukhanoff, CPF, Senior Director at Levi’s Strauss & Co, we’ll be talking about the above, as well as how to use size forecasting, optimized allocation, and visual analytics at IBF’s Business Planning & Forecasting: Best Practices Conference in Orlando USA, October 18-21, 2015.  I look forward to hopefully meeting you at the conference!  Your comments and questions are welcomed.