I wrote an article for the Journal of Business Forecasting a few years ago about dangerous habits that lead to software abandonment.  Since then I have reflected on the behaviors I’ve witnessed over my career and considered the stories others have told me about their journeys in change management. From this, I have developed some insights on why many find it hard to attempt digital transformations (or supply chain, planning or any other transformation) and succeed.

Transformations are challenging and are often loaded with what feels like more struggles than wins. When it’s done well, business processes benefit and our teams flourish. Unfortunately, most of us struggle or flat out fail in our transformation initiatives. So, here are some observations on why transformations are so challenging and suggestions on how to improve our chances of success. We will concentrate on new tools or software but the observations apply to most kinds of transformation.

Digital transformation is a series of large changes on a mass scale

First, intentionally doing a digital transformation by design is a change. It is not a minor change; it’s a series of large changes on a mass scale. Most people welcomes changes in others but are less enthusiastic when change is required of themselves.  In fact, they are often resistant to change and complain even about minor changes. My father has been known to say “I hate change” about something as trivial as upgrading his cell phone. Why then do we wonder why digital transformations are so hard, especially when we know so many do not like change?

While not all changes will be met with resistance, many—if not most—will. Just because we see value and in the proposed changes, we can’t assume that everyone else has the same understanding or expectation. One thing I have noticed in transformations that struggle or fail is a lack of properly set expectations and a failure to educate users.

Success Comes When Teams Know What We’re Doing & Why

We should educate users on why we need to change, not just on the mechanics of the change. Project education isn’t just a line item or a project statement. Rather than being a separate component, education should be a routine part that starts at the beginning of the project. Success comes when our teams understand what we are doing, why we are doing it and, most importantly, how it will benefit them.

This kind of education isn’t communicated within a formal classroom structure, but in the everyday conversations you have with users of the final solution. If your conversations during the transformation are limited to a core group of ‘superusers’ that excludes all end users, you may already be set up to fail.

Assign a Change Champion

A common theme of failed transformation projects is the lack of a change agent or a change champion. The change champion should not be a consultant or leader from another team or from a separate part of the organization. While it’s important to have the right implementation partner, they are not the change champions either.

Instead, change champions are team members who facilitate the transformation. They should be respected individuals from among the users who will embrace the change, share excitement for the new software and be able to demonstrate the new solution. Change champions listen to users and communicate requirements or bridge the gaps for the team. They should have the ability to convince other employees to use the new tools.

Change champions listen to users and communicate requirements for the team

It’s very difficult to have a successful transformation journey without a change agent or change champion. If you’re struggling with launching a transformation project, you may be missing this critical team member.

One organization I worked with had attempted to implement new planning software on three or four different occasions but ultimately failed at various points in the journey. They had a lead for the project and yet struggled. It wasn’t that this person wasn’t influential or a good leader, however, in this case, there was one Planner with equal clout that was incredibly resistant to any software change and prevented the launch of the new tool.

On the next attempt to implement advanced planning software, we knew we had to do some things differently to succeed. We added a new change champion, expanded the project strategy to include a business intelligence solution, and included process change to supplement the planning software. While the same user put up a roadblock and refused to use the new tool, we were still able to successfully launch by creating a strategy that supported the business and allowed the organization to launch the tool while working around the resistant user.

Build Process Maps

Another cause of transformation failure is the lack of understanding of the current state compared to the desired future state. Especially in an implementation that involves new software, part of the change involves moving to a new tool with enhanced capabilities.

When we fail to understand the differences between our current process flow and our to-be process flow, it is incredibly difficult to create a transformation roadmap that will lead to the desired to-be state. One of the most basic elements is to have process maps defined for both the current state and the desired future state.

A basic element is a process map for the desired future state

Process maps provide clear visibility into what must be implemented immediately and what can wait for a future enhancement. Digital transformation success is dependent on having a clearly defined future state process. Without it, the tool isn’t likely to be configured to support the desired future state. The journey may be made of one giant leap or many mid-size changes and mini launches.

Don’t Allow New Tools To Be Used For Old Ways of Working

Finally, I think most of us understand the importance of not using the design of the current tool for the new tool. However, the reality is that many teams fall into this trap. This is probably my biggest pet peeve when joining new teams who are at the end of a digital transformation or have just completed one.

This always creates issues, including some that will felt for many years to come. In such cases, the new tool is being forced to behave in ways it wasn’t designed to work. This results in a tool that is clumsy, slow and ultimately doesn’t support the desired to-be process or future growth. Despite good intentions, this can really derail long-term business success.

Encourage users to describe the behaviors they want to see

Often this comes about as users want to be sure to get their favorite functionality in the new tool so it works just like the tool they currently use. Be wary of having to implement functionality just because it exists a certain way in the current tool.

Instead, encourage users to describe the behaviors they want to see and how they’d like to view those results. Then, compare that need to how the new tool is designed to work and implement accordingly.  In my opinion, combining this strategy with process maps improves chances for a successful transformation.

In Summary

I haven’t yet found the key to secrets to make transformation projects easy or guarantee success. However, I have observed some common themes in transformations that struggle or fail outright. The biggest opportunity common to all of them was the need for a change champion with a clear vision of the destination and who can generate excitement for the project.

Having a change champion doesn’t lessen the importance of educating users—ideally, the change champion also leads user education. Change champions are also the experts that need to understand and be able to communicate process maps for the current state and to-be states. The best change champions also make a conscious effort to avoid imposing old tool designs and processes onto new tools, identify strategies to transition between current and future states, and become the enabler for change.  Failing at any or all of these can result in user resistance, inefficient workflows, hindered growth and even stalled or failed projects.

This article first appeared in the summer 2024 issue of the Journal of Business Forecasting. To get the Journal delivered to your door every quarter, become an IBF member. Member benefits include discounted entry to all IBF training events and conferences, access to the entire IBF knowledge library, and exclusive members workshops. 

Recent upheavals in global supply chains and changes in consumer behavior have taxed even the most robust processes used by elite planners on top tier software. Supply chain is the new buzzword, discussed in boardrooms and in mainstream media.

For sure, it’s a great time to be in planning. We know demand planning is the backbone of our supply chain and S&OP is the nervous system that makes it function.

But many times, we fail to give it the necessary attention or perform preventative maintenance to keep our demand planning and S&OP in top condition. Knowing it’s importance and value to the organization, now is a great time to reevaluate the planning tools we use, processes we have including S&OP, and consider upgrading our own skills.

Planning Tools are Good, but…

In this post, I’d like to offer some considerations when looking at the systems, processes and people that manage our planning processes the next time you need to drive improvements.

If we aren’t maximizing the value of our current software, then what makes us think a new one will produce better results?

Too often, we think we need a new tool or the latest software. Maybe that’s true, but my experience suggests that most of us aren’t taking advantage of the functionality offered in our current tools. If we aren’t maximizing the value of our current software, then what makes us think a new one will produce better results?

Most demand planning software use the same sets of algorithms and have comparable functionality

Most demand planning software available on the market not only use the same sets of algorithms but often have comparable functionality. Comparable functionality might include the ability to allow the software to recommend a best pick model, forecast simulations, manual forecast overrides, and outlier detection.

Most of them typically use some sort of internal sources of data like order bookings or shipments and all use varying time increments for forecasting and measuring results.

However, they can differ greatly in types of data available to build models (internal, external, structured, and unstructured data), user ability to interact with the data, segmentation, metrics and even how results can be shared.

Replacing existing software with something new is expensive. The cost to replace software includes not just the initial investment of a onetime implementation fee, but also ongoing subscription fees and costs relating to ongoing training, system enhancements and maintenance.

Before making that investment, make sure users understand how to use the existing tool

Before making that investment, take the time to evaluate the current tools and make sure users understand how to use the existing tool and see if there’s additional functionality your tool offers for the business to use. You own this tool, why not first explore maximizing the value of the existing software?

Examine Your Processes Before Spending Money On New Bells & Whistles

Next, before rushing to replace that tool, evaluate your processes. Complicated or highly manual processes will undermine the efforts of even the most sophisticated software.

Replacing one software for another while continuing to use the existing complicated or inefficient processes will, at best, let us get the same (or perceived better) results faster. That may be worthwhile in the immediate future, but it won’t be long before we’re back in the same situation looking for something “new” to fix our problems.

Another way to look at it: my new software gave the appearance of fixing the issue since I got the results, I thought I wanted, faster, but it failed to address the underlying issues creating the initial problem.

Instead, we should be just as critical of our internal processes, corporate behaviors, and policies as we are to the tools currently used to drive the business. Process issues not only increase the time in our demand planning and S&OP cycles – they also impact the speed of our software and general confusion in the business.

Understanding our process and the relationships it has with our tools is a critical component in understanding if we need a new tool or perhaps, we should re-implement or change how we use the current one.

Check Your Team’s Skills Relative To Industry Standards

One last thing to consider are the skills and knowledge of our planners. We have a team of skilled forecasters but where do their skills lie? For example, they could be skilled in how our company has always done business but not really understand industry best practices or the interconnected relationships with the software.

Our forecasters could be new to forecasting or maybe even veterans loaded with industry experience, but not really understand how our organization runs its business. Just like with processes and tools, skills of our people are equally important in determining the success or failure of our demand planning and S&OP processes.

Understanding the skills of the people currently running our process, and comparing them to the skills we believe we need in those roles, can prove enlightening.

No matter where individuals on your team fall (forecast newbies to veteran planners), having your team network and collaborate with industry peers, participate in conferences and other events, and seek ongoing professional education creates better understanding and provides opportunity to improve their processes. Encourage planners to seek opportunities to learn the new skills needed, perhaps consider being certified as a CPF (Certified Professional Forecaster) with IBF!

Reinvigorate the Tool, Tweak the Process, or Upskill Your Talent?

Demand planning and S&OP are critical in the value they provide to the success of the business. As we function in this highly variable, global market, it’s imperative that we keep up with the latest software and technology available.

However, it’s equally important to keep driving process improvements and keep the knowledge and skills of our planners up to date. Improving demand planning and S&OP processes and increasing their agility is necessary to keep up with the rapidly evolving global market. Ask yourselves if it’s time to reinvigorate the tool, tweak the process, or upskill your talent.

Misty will be speaking at IBF’s Global S&OP & IBP Best Practices Conference in Chicago from June 15-17. You’ll learn the ingredients of effective planning, whether you’re just getting started or are finetuning an existing process. Early Bird Pricing now open – more details here.

S&OP processes always include a demand review step. There are plenty of articles, webinars, and blogs about how to set up and optimize a Demand Review, covering such topics as the best metrics to use, which departments to include, and whether to use a unconstrained or constrained demand forecast.

These details are important, but there is something often overlooked in our attempts to build a robust Demand Review. We often struggle to speak a “language” that is understood by those outside Demand Planning.  By failing to speak a universal language we our peers can undervalue our efforts and fail to see how what we do  relates to their work.  As a result, we struggle to keep Sales and Marketing partners engaged and, subsequently, we don’t get the necessary insights.

Details are important, but the priority for our Demand Review meetings is cover four key areas. Let’s look at the cornerstones of a healthy Demand Reviews and identify what value should be captured from each of them, including the one even experienced Demand Planners miss that is key to tying our demand plans to revenue.

1 – Understand The Assumptions Behind Past Performance

To start, we need to understand the value of our past assumptions. These assumptions include understanding our demand history, quality of the data, the models we use to create statistical forecasts, and the adjustments we made to accommodate business changes. We can’t possibly build trust in the forecast we are using if we don’t take the time to measure and track past performance. It’s why we have so many discussions around which metric is best, which level to measure, and how to apply formulas.

“Too much time is spent reporting performance as if this is the purpose of the meeting”

Understanding past performance is necessary, but frequently too much time is spent reporting performance as if this is the purpose of the meeting. Capture it, measure it, discuss it but don’t spend all your time on it. It is equally important to take the time to choose the right metrics. While a single metric can certainly tell you something valuable about the forecast, a singular metric limits understanding and often generates misconceptions about the forecast. Using multiple (compatible) metrics improves daily decisions when using the forecast.

This article isn’t to debate which measure is best, which formula to use or how to apply them; it’s a reminder to consider metrics beyond just looking at accuracy and bias. There are plenty of great metrics that you should add like FVA, Forecastability, tracking signals and waterfalls, forecast hit/miss, and even simple absolute error in dollars. Whatever combination you choose, explain the metric in terms of what they measure and what they tell you about the data. Advanced planners will take the time to link results to actionable behaviors in other areas.

“Discuss past assumptions and which ones were most value-added”

For example, forecast performance can explain poor service levels, tendency to build excess inventory (bias), or even why operational efficiency is low (poor product mix measured by accuracy calculated at lower levels). Measurements like FVA can tell us which assumptions, forecast or whatever we want to measure provided a better predictor of actual demand. Discuss past assumptions and which ones were most value-added.

2 – Assess The Current Demand Factors

Secondly, we need to understand our current demand situation. The Demand Review should also highlight our current immediate forecast and help us to understand how we are trending in actual performance. While this isn’t the ultimate focus of our meeting, it is something we should discuss. Are we waiting on orders or are orders ahead of plan? Is there a risk of creating future shortages?

Reviewing and discussing the current short term demand picture can also help us identify unplanned and previously uncommunicated events. Finding these events while they are happening — while less than ideal — can help us mitigate risks and drive better customer service in the future than if we were to find them when reviewing our past assumption performance.

Of course, it would be better to be told of these events in advance so they can be properly planned, but let’s face it — for every event or planned promotion there is at least as many and usually more that happen on the fly without any advance notification.

3 – Understand Future Demand Factors

Our Demand Review should help us understand the future. Most of our time should be spent on understanding the assumptions, events, new products, or sunsetting items loaded into the demand plan in the mid to long range period, as well as any risks or opportunities in that plan. Rather than thinking about the forecast for next week, next month or maybe two months out, we should be looking out to the next quarter or the next year in our forecasts. At a minimum, we should be looking at our max lead-time plus one period.

“The Demand Review creates a road map that all other departments in the organization will use to make decisions”

I’ve been in many Demand Reviews and have been guilty of leading reviews where most of our time was spent on looking at past performance. Sure, it helps us to understand something about our process, we must give at least equal attention to the future. The whole reason we’re building the demand plan is to have some understanding of what we can expect in the future and to share that knowledge with the rest of the organization. It’s to set a road map that all other departments in the organization will use to make decisions.

Understanding the assumptions and any risks or opportunities that exist provides context, credibility and builds trust in the forecast, which is critical if other functions are to use it. Thus, when using the demand plan, we can plan contingency strategies for things not in the plan instead of letting fate happen.

4 – Understand The Gap Between The Demand Plan & Financial Plans 

One last part often missing from demand reviews is a gap analysis between the demand plan and the operating budgets or financial plans. We work as a team towards a single plan, but those forecasts may look different depending on how they are translated such as the difference between the demand plan, financial plans, and the replenishment plan. As the demand plan rolls through the S&OP process into the supply review, disconnects between what we sell and what we can supply are identified and addressed. Unfortunately, we often overlook the need to compare the demand plan to the latest operating budget or financial plan.

It’s not just about comparing to the original plan from the beginning of the year — that will no doubt change — but instead understanding the gaps between the current financial plan and the demand plan. Are we planning for revenue above what’s in the demand plan? If so, what is being done to ensure the right product (or any product) will be available to sell to meet the revenue expectations? If revenue expectations are below the demand plan, do we understand why, and the potential excess inventory we are building? Communicating and understanding gaps improves opportunities to meet corporate initiatives.

Demand review are a critical step in any S&OP process.  As Demand Planners, we often get buried in a lot of details with large charts and files, talking about metrics that many of our sales and marketing partners may not understand or find valuable. Taking the time to communicate the right metrics and refocus efforts on the parts that matter most will result in a more productive demand review meeting.  It’s not about who is the most accurate, but rather identifying the data that provides the most value and capturing the insights needed to better run our business.

Keeping up with available technology and being able to respond to the rapid changes in the market make it necessary for organizations to adopt “new” planning software including enterprise resource planning (ERP) tools.

Hours of work are put into getting approvals, securing financing, building excitement, and getting support of the organization. Once launched, it’s easy to think we’ve succeeded since we’ve passed the hurdles of approval, selection and launch. Much emotional energy has been spent discussing the frustration and failures of the old software while customizing and launching the new. Users are excited for the new software and the perceived promise it will fix all our issues or at least certain issues.

Practically speaking though, users are excited until they get through the initial honeymoon phase and now realize they must use the new tools and make changes to their daily workflow, habits and schedules.

When processes and tools have been in place for years or even decades, change can be especially challenging. As a result, the new software we’ve just launched could be in danger of being abandoned with unintentional self-sabotaging behaviors. The following details common post-launch behaviors that, if unchecked will limit the ROI of any investment in technology.

Behavior 1: Treating The Software Like A Black Box

Launching new software is both hard work and exciting. Because of this excitement, any time users discuss the results, reports and metrics produced by the new software, it gets both the praise and the blame. Conversations will typically start with “new software says…” as if the new software was to blame for the poor result or is the sole reason for success. The new software may have an issue in calculation, formula or connection, but with post launch support, these are usually quickly resolved and fixed. Unfortunately, this language continues long after any bugs and errors in the software have been corrected.

When used indiscriminately, especially for negative results, our customers distrust the new program and start longing for “the good ole days”, forgetting the issues they had before. We must give our internal stakeholders a reality check—if the software is operating correctly, it’s only providing the results of the data supplied based on the assumptions loaded, and it isn’t a mysterious black box. In other words, if you don’t like the results, there is either a data issue, or an assumption has changed and is no longer applicable.

These assumptions are more than just the forecast (although the forecast or demand plan is important) but may include other factors such as lead times, cycle time, capacity, variability, yields, bills of material, minimum order quantities or even item attributes such as case pack, cost and many others.

New software usually provides expanded capabilities and visibility to the organization. It has better algorithms, calculated assumptions like demand or supply variability and may even have additional fields not available in the primary system of record. The improvements provided by the new software typically provide solutions to the weaknesses of the old planning tools. Forgetting the new features and failing to remember or understand how they work negatively affects perception of both the new software and reputations of planner’s abilities and knowledge.

Rather than constantly saying the “new software says,” try changing terminology to “per data,” or “based on our current plan.” Both of those recognize the power within the organization to control the results rather than the new software seeming to operate independently as a black box.

Behavior 2: Training Just Once On The New Software

Users typically receive extensive training as part of their pre-launch activities. However, that is a lot of information crammed into a very short period, including how to do regular daily activities in the new system and how to use the exciting new features. Unfortunately, there’s so much data even the most tech savvy users will struggle to remember it all, let alone use it in the months post launch.

Post launch, users are busy trying to apply the new tools to their daily jobs and keep the business running. If continued post-launch support and training is offered, it’s either limited to a few super users or isn’t fully taken advantage of by the team. Failing to offer post-launch training and refreshers is a missed opportunity to help users incorporate the new tools into their daily activities and inhibits long term success.

Many a software platform has failed or been abandoned not because users aren’t willing or because it isn’t working, but because it isn’t being used to its full potential. In general, without continued support, users may find it easier to fall into old habits because it’s familiar and using new tools is time-consuming and, initially, difficult. User training including refreshers and enhancements post launch is critical to long term success and organization adoption. Continued training provides the best opportunity to maximize user abilities, process improvement and future enhancements to the new software to meet the evolving needs of the business.

Behavior 3: Failure To Celebrate Wins—Even The Little Ones

An important part of any new system launch is understanding how success is defined. Defining what success will look like pre-launch using goals and desired target results can provide the tools necessary to help change negative perceptions by reminding the organization of where we’ve been, and the improvements made. The desired targets should include a broad spectrum of goals surrounding implementation, such as hitting launch timelines, user acceptance or adoption rate, and business goals, such as KPI improvements pre vs post launch or new metrics available as a result of the new software.

While big celebrations are typically done for big milestones, it’s just as important to celebrate and provide recognition for the small everyday improvements that may not be as easy to measure such as time saved or improved process visibility. Little win celebrations in the months after go-live are big opportunities to continue to sell the new software to casual users.

Behavior 4: Measuring Success In A Vacuum & Ignoring The Complete Picture

Measuring successes—both big and small—is necessary. However, be wary of attributing too much importance to any one measure, especially any measure in isolation. For example, it would be easy to say we have more on hand inventory than last year and therefore the new software isn’t working. However, if holding more inventory meant taking advantage of opportunities with customers and making more sales, fewer stock outs, and improved service levels, then the statement more inventory equates to a failure by the new system is misleading. Yes, inventory is greater than last year, but increased inventory was necessary to meet the other goals set by the organization.

When we make big changes, it takes time to see the long-term impacts on the business. Setting appropriate expectations for what will happen post-launch helps manage expectations. Unfortunately, there will be times members of the organization will get hyper focused on a single metric. “Single metric mindedness” may be normal but making the effort to keep the focus on the broader scope and agreed upon measures of success is necessary to prevent abandonment of the new software.

Conclusion

Hyper focusing on a single measure to define success of new software, especially by those in leadership roles, is dangerous. Instead, refocus efforts by regularly reporting and celebrating results—even the little wins. This maintains focus on how much positive change was brought about by the new software as well as providing a realistic and comprehensive view of performance.

Adding consistent, frequent user support and training post launch gives the organization the best opportunity to not only take advantage of the new software but to identify any future improvements that may be needed due to the natural changes in business.

We must be especially mindful of how we speak about the new software as this positively or negatively shapes user perception. Positive speech has the potential to reap enormous rewards not only regarding longer-term adoption of the software, but also confidence in user expertise and the organization’s planning processes.

Misty will be sharing further insight into forecasting and planning 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.

Using history to predict the future is the most basic assumption that underlines demand planning processes and activities. This assumption presupposes that there is inherent demand variability in sales and, by analyzing sales data, the variability can be identified and managed – that is a given. But it’s not only demand planners who must understand variability; Supply Planners also need to be proficient in identifying factors that impact supply and then manage them to mitigate risk.

Not All Risk Comes From Demand

Supply planners must look internally and understand that not all risks come from demand. Risks and variability in the supply chain are often viewed as a forecast problem but the forecast isn’t the only part of the supply chain that features variability, and demand assumptions aren’t the only assumptions driving our supply chains and S&OP. 2020 has been a year that has really highlighted the need to manage assumptions across the entire supply chain and not just for demand.

Understanding Supply Chain Variables

Assumptions exist outside of demand. They impact our ability to serve our customers and need to be identified and managed, just as we do with demand assumptions. Attribute data (data relating to those things that cause variability in supply) related to an item’s characteristics, distribution network, manufacturing process, purchasing terms, and even general planning settings, all contain variables that impact the supply chain.

We have an opportunity to introduce previously unrecognized uncertainty into the supply process.

Typically, these factors aren’t considered to impact supply. Often these attributes are poorly managed and unvalidated unless persistent and serious issues make them impossible to ignore. When we input this data into the master data of planning systems, we have an opportunity to introduce previously unrecognized uncertainty into the supply process. When we do this, we get visibility into supply constraints and are in a position to manage them.

Failure to understand these supply assumptions results in either a growth of excess and obsolete inventory or in a shortage of good inventory,

This data (or attributes) should be regularly reviewed for accuracy, tracked for performance, and actively managed and maintained. For example, we must understand the impact on supply performance when lead times, run rates or process times change, or minimum order quantities and lot sizes are greater than our total annual forecast, or when any other supply constraint appears. Failure to understand these supply assumptions results in either a growth of excess and obsolete inventory or in a shortage of good inventory creating customer dissatisfaction and service failures.

Variability In Demand Is Often In Fact Variability In Supply

When things don’t work out as planned from a supply chain perspective, we often assume it’s due to a random, non-repeating event that could not be prevented when in fact there were indicators in the data that could have alerted us to it ahead of time. Key attributes impacting our supply chains should be identified to reduce unplanned variability and poor performance. They should be measured for accuracy and adherence to bring about best supply results. Unfortunately, when this is not done it shows up as variability in demand! 

We know there are many circumstances that can change the results of attribute values both internally (labor availability, repairs, inaccurate inventory) and externally (weather, transportation limits, vendor capacity). Measuring supply performance and communicating this performance and its drivers back to demand can help demand planners better manage forecast variability. Loading supply settings without validating if they are correct restricts the value demand planners add and that of the demand plans they generate.

Scenario Planning Requires Properly Managed Supply Assumptions

Properly managed supply assumptions create better scenario planning. Scenario planning is a useful part of the S&OP process that aims to maximize margins and profitability. Many of us already create scenarios based upon various demand expectations, but we should also create scenarios based upon potential supply changes. Understanding how adding an extra shift impacts inventory is just as important in reaching our goals as understanding what happens if customer X sells 40% more than planned.

Taking the time to understand the assumptions outside of demand allows us to create scenarios and understand potential financial risk to the business. Understanding variability in supply and how we are performing against expectations will certainly improve the quality of the scenarios we run in S&OP.

I believe demand planners need to teach supply planners how to recognize and manage assumptions.

Bottom Line: Supply Planners Can Learn Much From Demand Planning

I believe demand planners need to teach Supply Planners how to recognize and manage assumptions. Not only that, like Demand Planners, Supply Planners should also be held responsible for understanding and managing variability.

Metrics may be different between demand and supply, but they have the power to work together to reduce it. Supply planners must understand why there are differences between planned and actual results, find the root causes of the differences and understand when we might see changes in the future that don’t adhere to standards. When we fail to manage supply variability, we introduce additional variability not just into the supply plans but also into the demand plan, resulting in inventory imbalances and poor service levels.

If you haven’t defined which supply attributes are key in your supply chain, 2020 is the year to take a leaf out of demand planning’s book and start defining, reviewing, and measuring them and incorporating them into your process as core assumptions.

Last year I attended IBF’s conference in Orlando on demand planning, forecasting and S&OP with many peers and industry leaders. During the leadership forum, we had an opportunity to break into groups to discuss the key steps of S&OP – product review, demand review, supply review and executive review. I was surprised that that the product review step was the part of S&OP that most attendees found challenging, or were unfamiliar with.

S&OP has been around since the late 1980’s. The process has been traditionally about balancing supply and demand to support the strategy needed to meet company goals. Many books and articles have been written over the years about the S&OP process, how to implement it, and how to make it better.

Generally, it has been a 5-step process that centered around tactical activities: data gathering, demand planning, supply planning, pre-S&OP and an executive review. Over the years, the process has evolved and even been called new names like SIOP (Sales, Inventory & Operations Planning) and IBP (Integrated Business Planning) among others with the addition of other business functions (such as inventory and finance).

In the last few years those steps have become process activity oriented: product review, demand review, supply review, pre-S&OP and an executive review. In the change from tactical to process oriented steps, it appears that a new review has appeared – the product review.

Why You Need A Product Review In Your S&OP

While demand and supply balancing addresses the economic factors facing the business, the product review and lifecycle review processes address the strategy and product portfolio we want to offer the market. Product review and lifecycle processes are not new and exist in most organizations but they are frequently independent of the S&OP process. If the product review cycle is not a part of your existing S&OP process, it should be. Let’s look at some compelling reasons to integrate the product review into your S&OP process.

If the product review cycle is not a part of your existing S&OP process, it should be.

1. You Get A Single Corporate Product Strategy

A product review should be exactly as it sounds, an analysis of the lifecycle of each item in our product portfolio to determine the future sales strategy of each item. Development and launch of new items are managed with project timelines, market analysis and launch forecast, while items slated to be discontinued due to declining sales are managed separately in item lifecycle reviews. The product review, therefore, is the strategy for each item into the future.

The product review is the strategy for each item into the future.

Including the product review as part of the S&OP process and integrating with demand and supply allows us to control our destiny as a company and provide the best opportunity for success. Our demand and supply plans encompass not only our current business but allow for improved visibility into changes in the business going forward. All aspects of the supply chain can anticipate changes to the portfolio enabling a single cohesive conversation that prevents overlooked challenges and opportunities. Anticipation of consumer demand improves when we know what sales is selling to our customers. A single corporate product strategy reduces competing priorities between departments and reduces disruptions to our customers.

2. Product Review Means An Improved Demand Plan

Integrating the product review into the demand review process improves the forecast. Demand planners really are experts at managing assumptions. A most common assumption, which is also used for all time-series forecast models, is that sales history can be used to predict the future. That’s true but demand managers can enhance this by applying other assumptions into their demand plans and make improvements to the forecast. Other assumptions might include changes in customer mix, market intelligence or the impact of inventory stock outs on past sales. When they include the results from the product review, demand managers can also look at how changes to mix of items sold impacts the forecast.

Demand managers can focus on improving the timing and magnitude of anticipated product changes instead of just reacting to changes in sales.

Now the demand manager can also consider cannibalization impacts between items when a new item launches, and also the impact when an item is discontinued. Each managed assumption has the potential to improve or hurt the business and can be easily captured in the KPIs you use in your S&OP process. Including the results of the assumptions from the product review tends to improve the quality of the resulting forecast and allows for capture of mix changes before they happen. Demand managers can instead focus on improving the timing and magnitude of the anticipated product change instead of just reacting to the change in sales. Demand becomes more predictive and less diagnostic and descriptive in the process!

3. You Get Improved Supply Performance and Inventory Plans

Supply planning is usually the last department to know about any changes to items including new product launches, distribution changes or even item discontinuations. By including the product review in S&OP and as part of the supply review process, supply and inventory plans can be tied to the product strategy. As a result, replenishment plans that were created on the historical product mix can be corrected to cover the current or future mix of items being sold to customers. The supply review can properly plan and replenish the right inventory volumes at the right time on the right items for future sales.

Planners can set safety stocks and replenishment strategies that support the overall future corporate strategy.

Planners can set safety stocks and replenishment strategies that support the overall future corporate strategy. Manufacturing, purchasing and logistics have improved opportunities to identify bottlenecks and communicate those risks back into the S&OP process. As a result, overall inventory levels are managed across all items. New item inventory is available on time while inventory for discontinued items can be reduced before customers stop ordering.

Ultimately, the goal of any S&OP process is to enable better decision making and support business decisions. To do this, the S&OP process has three key parts: strategy, demand and supply. The product review should be a key part of any S&OP strategy and plays a defining role in the results of the demand and supply review steps.

For S&OP to be successful, defining the product portfolio and managing item lifecycles are crucial. Communicating the results of the product review as part of the S&OP process adds clarity and improved opportunity for success. Making the product review process an integral part of the S&OP process keeps all parts of the organization focused on a single product strategy and the critical items needed to support the long-term corporate goals.

Misty will be speaking on this topic at IBF’s Business Planning, Forecasting & S&OP Conference in Orlando from October 20-23, 2019. Join her and a host of other planning, forecasting and analytics leaders at the biggest event of it’s kind for learning, networking and more.