“Perfection is the enemy of progress.” – attributed to Winston Churchill

Disciplined Sales and Operations Planning (S&OP) has long been recognized as a transformative process for aligning demand, supply, and finance with long-term strategic goals, providing a single, integrated view. For many organizations, the promise of S&OP is very compelling in its potential to achieve improved service levels, lower costs, better overall alignment, and faster, data-based decisions.

So, then, why do so many companies stall or fail in their S&OP implementation efforts?

First, the bad news: one common culprit is perfectionism. A fully mature S&OP process that functions flawlessly on day one simply does not exist, and an organization’s pursuit of perfection before implementation often becomes the very reason nothing meaningful gets launched at all.

The Trap of the “Perfect” S&OP

All too often, organizations defer S&OP implementations until:

• All data is available, clean, and integrated across all systems
• Forecast accuracy is “high enough”
• All stakeholders are on board and trained
• The “perfect” KPIs are defined
• Executive leadership is 100 percent aligned

These are all worthwhile goals — but they should not be prerequisites. After all, a well-designed S&OP program, geared toward continuous improvement, can help address, or even resolve, these very concerns. If company leadership’s demand for a perfect process becomes the bar for starting S&OP at all, there’s a high probability that it won’t ever actually happen.

Overused analogy aside, S&OP is a journey, not a single release event.

Start Small Rather than Waiting for Perfect

When companies choose progress over perfection, they quickly gain:

• Momentum: Small wins build credibility and energy
• Learning: Real-world feedback reveals what’s important
• Buy-in: Success breeds adoption, even from skeptics
• Clarity: You see which data, metrics, or tools are truly essential
• Flexibility: Each cycle identifies course corrections for the next

Why Good Outperforms Perfect: A Simple Case Study

One organization delayed its S&OP for six months, waiting for IT to complete a custom dashboard. Another kicked off with a simple spreadsheet showing demand vs. supply for their top ten items. Within two weeks, the second group was having better discussions — and catching issues early. Six months later, their process was more advanced than the one still waiting for perfection.

Keys to Making Progress Now

Launch, or relaunch, your S&OP process without falling into the perfection trap:

1. Start with what you know: Use existing data and systems.
2. Focus on issues and decisions, not documentation: The goal is alignment, not reports.
3. Engage the right people: Cross-functional doesn’t mean everyone — just the key voices.
4. Set a cadence and stick to it: Monthly reviews with a clear agenda are enough to begin with.
5. Be transparent about gaps: Call out data issues, assumptions, and tradeoffs — it builds trust.
6. Make iteration part of the plan: Document learnings and evolve over time.

Progress Is the Path toward Perfection

“Perfect is the enemy of good.” – French Philosopher Voltaire

There’s nothing wrong with aspiring to have a best-in-class S&OP process. But this doesn’t come overnight — it’s achieved through consistent progress.

• You can’t optimize what doesn’t exist.
• You can’t refine what hasn’t been tested.
• You can’t learn until you’ve started.

So start now. Start simple. And improve relentlessly.

Because when it comes to S&OP, good can be more rewarding than perfect, especially when it leads to more rapid alignment and better decision-making.

In today’s volatile and uncertain market, companies can no longer afford to operate without a structured, data-driven approach to forecasting demand. Demand planning is more than just predicting sales—it’s about building an integrated, agile business that can respond to customer needs while managing resources efficiently. Despite its importance, many organizations still rely on outdated tools like spreadsheets or allow bias and siloed decision-making to corrupt their forecast accuracy.

Employing predictive analytics and integrated demand planning can significantly streamline decision-making processes, create new insights, and save several business functions a lot of time and money.

This article explains why businesses need to leverage demand planning to improve their operations and explains the quantifiable value of doing it so that it can be sold within an organization.

Why Focus on Demand Planning?

Most companies that decide to invest in demand planning or improve their process are primarily driven by one or more of the following:

• Forecast accuracy challenges
• A highly variable process that needs improvement
• Need for a more efficient manufacturing or distribution system
• Downstream inventory problems driven by unseen variability
• Desire to improve cooperation between sales and operations

At its core, demand planning synchronizes operations. It allows marketing, sales, supply chain, finance, and production to operate from a common set of assumptions. Without an accurate demand plan, supply planning becomes reactive, finance struggles with forecasting revenue, and customer service deteriorates from stockouts or excess inventory.

Consumer behaviors have become increasingly unpredictable. Economic shifts, global disruptions, and rapid product cycles mean relying on historical sales alone is no longer sufficient. Demand planning introduces a proactive lens incorporating internal drivers (promotions, price changes) and external signals (market trends, customer insights) to create adaptive forecasts.

Inaccurate demand forecasts translate to costly outcomes: expedited shipping, excess working capital, lost sales, and markdowns. Improved demand planning helps reduce forecast error, allowing for better inventory placement, production planning, and supplier coordination. Even a five to ten percent improvement in forecast accuracy can have a significant bottom-line impact.

Potential Improvements Resulting From Demand Planning

Organizations that invest in improving demand planning benefit from:

• Reduced inventory costs through better alignment of supply and demand.
• Improved service levels by placing the right product in the right place at the right time.
• Higher forecast accuracy can lead to more reliable plans across finance and supply.
• Faster decision-making is enabled by real-time data and scenario analysis.
• Greater agility because of the ability to quickly adjust to shifts in demand or supply.

A mountain of research today shows that a mature demand planning process helps improve forecast accuracy and deliver a high return on investment (ROI). Improved forecast accuracy, when combined with software that translates the forecast into meaningful actions, will decrease inventory and operating costs, increase service and sales, improve cash flow and gross margin return on inventory investment (GMROI), and increase pre-tax profitability. The forecasting error, no matter how small it is, significantly affects the bottom line. In our experience, a 15 percent forecast accuracy improvement will deliver a 3 percent or higher pre-tax improvement.

In a previous IBF study of 15 U.S. companies, we found that even a one-percentage-point improvement in under-forecasting at a $1 billion company delivers a savings of as much as $1.52 million, and for the same amount of improvement in over-forecasting, $1.28 million.[i]

The reduction in downstream finished goods inventory resulting from a well-established process and forecast accuracy improvements provides a one-time saving, as well as recurring savings arising from reduced carrying costs. There are great benefits in a make-to-stock or distribution company, the downstream inventory reduction could range from 10 to 20 percent since forecasting inaccuracies typically drive around 75 percent of the required safety stock.

Building and Investing in Demand Planning

Here are some best practices when it comes to demand planning.

• Build an unbiased, unconstrained, consensus-based forecast. Organizations often confuse the demand plan with the sales target. Sales may overestimate to push for stretch goals, while operations may buffer to protect service. Demand planning needs to separate judgment from aspiration. Instituting a formal demand consensus process ensures all voices are heard, but forecasts remain grounded in data and evaluated against actual performance.
• Upgrade from static spreadsheets to dynamic models. Many companies still use Excel as their primary planning tool. While familiar, spreadsheets lack scalability, version control, and real-time integration. Upgrading to a dedicated demand planning system (or enhancing existing tools with forecasting models) introduces automation, improves collaboration, and enables real-time adjustments. It also supports more advanced techniques such as decomposition models or AI-based forecasts.
• Understand and match models to patterns. Not all items follow the same demand pattern. Some are seasonal, some have trends, and others are highly volatile. Applying a one-size-fits-all model can lead to overfitting or underperformance. Instead, classify SKUs by their demand characteristics and apply the appropriate model, whether that’s exponential smoothing, moving average, or more complex causal models.
• Focus on data quality and forecastability. Forecasting is only as good as the data behind it. Cleanse data for outliers, missing periods, and promotions. Measure forecastability using the Coefficient of Variation (CV) or Demand Intermittency. The demand planner becomes the integrator, ensuring inputs from various departments are translated into a structured forecast. Establish accountability through KPIs like bias, MAPE, and forecast value add (FVA).
• Invest in training and improving skills with IBF. Leverage IBF’s certifications, workshops, and learning resources to empower your teams with proven forecasting and planning knowledge, building internal capability that drives consistent, confident decision-making.

Taking steps to practice demand planning optimally will increase the bottom-line benefits you gain from it.

Bottom Line Benefits for Practicing Demand Planning

Many companies leave money on the table with lost sales or poor service levels. An integrated demand planning process can translate to increased revenue of 0.5 percent to 3 percent with improved inventory availability or demand shaping capabilities. Total annual direct material purchase, along with logistics-related expenses arising from demand variability and lost opportunities, can see direct improvements of 3 to 5 percent. We can also benefit from a 20 percent reduction in airfreight costs. The figure below shows the anticipated benefits from a 15 percent improvement in forecast accuracy. (These are averages and individual results for organizations. They are dependent on many other variables and can be higher or lower.)

This illustrates the possible benefits from a 15 percent improvement in forecast accuracy

It is essential to understand that these are average savings amounts. It is up to you to determine what savings you believe you can drive with a mature predictive analytics and demand planning process. Sometimes you need to know what finance and executive leadership anticipate in terms of benefits; you need to be on the same page in terms of expectations. It is here that the Institute of Business Forecasting Advisory Services can shed some light on what is realistic based on past implementations.

Demand planning is not just a supply chain function; it’s a strategic business process that empowers smarter, faster decisions. In an environment where disruption is the norm and expectations are high, companies that implement disciplined, data-driven demand planning will not only survive but also lead.

The Benefits of Demand Planning: The Final Word

The path forward is clear: Separate judgment from strategy, invest in tools and talent, and build a collaborative process that evolves with your business.

In a world of uncertainty, demand planning offers clarity. It’s not just about predicting the future, it’s about preparing for it. Companies that invest in robust, unbiased, and collaborative demand planning are the ones that outperform, outmaneuver, and outlast their competition.

But you don’t have to do it alone.

The Institute of Business Forecasting (IBF) has been the trusted authority in forecasting, demand planning, and S&OP for over four decades. Whether you’re just starting your planning journey or looking to refine and elevate your process, IBF offers the training, certification, tools, and global community to help you succeed.

Join IBF and take the next step:

• Get certified with globally recognized credentials
• Attend industry-leading conferences and events
• Access exclusive research, case studies, and best practices
• Learn from and connect with top planning professionals around the world.

[i] Chaman L. Jain (2018). The Impact of People and Processes on Forecast Error in S&OP. IBF research report #18. August 31, 2018

Sales and Operations Planning (S&OP) is a structured, cross-functional business process that aligns all areas of an organization around a unified set of assumptions to drive coordinated decision-making. The goal of S&OP is to ensure that business plans and objectives are balanced and that financial and operational plans are synchronized. It serves as the critical integration point between strategic planning and daily execution, enabling companies to translate high-level business objectives into actionable plans.

At its core, a mature S&OP is not just a supply chain or operations process. It is a business-wide planning framework that brings together sales, marketing, finance, operations, product management, and supply chain to work collaboratively. The result is a comprehensive plan everyone supports and works toward, reducing misalignment, improving responsiveness, and increasing overall business performance.

The process typically operates on a monthly cadence, with inputs from various departments converging into a final executive review meeting where trade-offs are discussed, decisions are made, and a single, unified plan is committed to.

The Value of S&OP

Implementing and executing an effective S&OP process provides tangible value across the organization. At a high level, S&OP delivers:

• Improved forecast accuracy and demand visibility: S&OP allows companies to move from reactive to proactive planning, reducing surprises and enabling better preparedness for market changes.
• Balanced supply and demand: With cross-functional collaboration, companies can more efficiently manage supply constraints, optimize inventory levels, and meet customer service goals.
• Financial alignment: S&OP ensures that operational plans are financially viable and support the broader goals of the business. It connects demand and supply plans to financial projections.
• Increased agility: The ability to run scenarios and analyze the impact of decisions across the business improves agility in the face of disruptions or demand shifts.
• Enhanced collaboration: S&OP builds a culture of accountability and transparency. It fosters communication across silos and ensures that all stakeholders work from the same assumptions.
• Executive-level visibility: With clear insights into upcoming challenges and opportunities, executives can make informed decisions with confidence.

Organizations with mature S&OP processes often see improvements in service levels, inventory turns, working capital, and revenue growth. But the actual value lies in the enhanced decision-making capabilities and improved alignment across the business.

How to Build a Sales and Operations Plan

Developing a robust sale and operations plan requires a clear structure, defined roles and responsibilities, and a commitment to consistent execution. While tools and technology play a role, the foundation of effective S&OP lies in process discipline and cross-functional collaboration.

Here are key building blocks to consider:

• Leadership commitment: Executive sponsorship is essential. S&OP must be seen as a strategic business process, not just a supply chain activity.
• Defined ownership and governance: Each step of the process should have clear ownership, with defined roles for demand planning, supply planning, finance, product management, and executive teams.
• Calendar and cadence: A standard monthly cycle should be established, with defined inputs, outputs, and meetings for each phase. Concurrent weekly S&OP meetings help manage near-term deviations.
• Unconstrained and unbiased planning: The demand plan should be developed independently of constraints or biases, providing a true reflection of expected demand. Only then can supply plans be adjusted accordingly.
• Data and metrics: Reliable data is the backbone of S&OP. Forecast accuracy, bias, inventory health, and capacity utilization are some of the key metrics that drive accountability and improvement.
• Technology and tools: While not a prerequisite, modern planning tools can enhance collaboration, scenario planning, and automation. However, these tools must support—not replace—a sound process.
• Culture and change management: S&OP is as much about people as it is about process. Building trust, encouraging open dialogue, and reinforcing accountability are crucial for success.

Key Steps in S&OP

A typical S&OP process includes several structured review steps culminating in an executive decision-making forum. Here is an overview of each phase:

Product Review

• Purpose: Align the product and portfolio roadmap with business strategy.
• Activities: Review new product introductions, end-of-life plans, promotions, and phase-outs. Evaluate the impact of changes on demand and supply.
•  Participants: Product management, marketing, R&D, operations, and finance.

Demand Review

• Purpose: Develop an unconstrained, consensus demand plan.
• Activities: Analyze historical performance, market trends, customer input, and promotional plans. Identify risks and opportunities.
• Participants: Demand planning, sales, marketing, and finance.

Supply and Resource Review

• Purpose: Determine how to meet the demand plan with available resources.
• Activities: Evaluate capacity, inventory, procurement, logistics, and supplier capabilities. Highlight constraints and propose scenarios.
• Participants: Supply planning, manufacturing, procurement, logistics, and finance.

Pre-S&OP/Reconciliation Review

• Purpose: Identify gaps between demand and supply, align on scenarios, and prepare for executive discussion.
• Activities: Review financial implications, resolve issues, and recommend decisions.
• Participants: Cross-functional team leads, finance, and planning leadership.

Executive S&OP Review

• Purpose: Make final decisions, approve the consensus plan, and provide strategic direction.
• Activities: Review scenarios, validate financial impact, approve trade-offs, and document decisions.
• Participants: Executive leadership, heads of major functions, and finance.

Concurrent Process: Sales & Operations Execution (S&OE)

While S&OP focuses on the mid- to long-term horizon (typically 3 to 24 months), S&OE manages near-term execution (0 to 13 weeks). This weekly process addresses short-term deviations from plan and ensures agility in responding to real-time changes. Key focus areas include order fulfillment, short-term supply imbalances, and demand shifts. S&OE connects strategy to execution, ensuring that decisions made in S&OP are implemented effectively.

Sales and Operations Planning: The Final Word

In today’s complex and volatile business environment, Sales and Operations Planning is more than just a process—it’s a mindset and an essential capability. Companies that embrace S&OP gain the ability to navigate uncertainty, align cross-functional teams, and drive smarter, faster decisions.

The future of S&OP is one of greater integration, intelligent automation, and real-time visibility. But, at its heart, the success of S&OP will always depend on three things: collaboration, transparency, and consensus.

Organizations that invest in building a strong S&OP process—supported by leadership, informed by data, and aligned with strategic goals—will be better positioned to thrive. They will not only deliver superior performance but also foster a culture of shared accountability and continuous improvement.

In short, Sales and Operations Planning is the bridge that connects strategic intent to operational execution. Done right, it becomes a sustainable competitive advantage.

Do you have questions about demand planning? This guide explains everything you need to know about this complex topic in a simple and understandable way.

What is Demand Planning?

Demand planning is the process of using analytics, data, insights, and experience to make predictions and respond to various business needs. It leverages demand forecasts—not as an end in themselves—but as a tool to highlight opportunities and risks, establish business goals, and support proactive planning across functions.

While demand planning often reports into the supply chain, it is not solely a supply chain function. It is a cross-functional discipline that integrates insights from sales, marketing, finance, and operations to create a consensus plan—a unified view of what is most likely to happen in the market.

Demand planning combines historical sales analysis, market intelligence, consumer behavior trends, and business knowledge to guide actions across the organization. It enables companies to anticipate demand shifts, align resources accordingly, and avoid stockouts and excess inventory, especially in an environment where customer expectations and market conditions constantly evolve.

At its core, demand planning drives better business performance by ensuring that decisions are based on relevant, timely, and collaborative inputs, not guesswork or isolated projections.

Bottom line: An accurate demand forecast provides the information your operations and sales teams need to plan how much product to buy or manufacture to meet projected demand as efficiently as possible with limited waste.

What is the Difference between Demand Planning and Demand Forecasting?

Demand forecasting and demand planning are closely connected but serve different purposes:

• Demand forecasting is the analytical process of using data, statistical models, and judgment to predict future demand. It’s a probability-based estimate of what might happen and forms the foundation for planning decisions?
• Demand planning takes the forecast further by integrating it into the business strategy, aligning stakeholders around a shared set of expectations, and determining the actions needed to respond to that demand.

What Purpose Does Demand Planning Serve?

Demand planning aims to create a realistic and actionable view of future demand so the organization can align supply, resources, and investments accordingly. It addresses critical issues including:

• Strategic planning and assessing risk (long-term planning and S&OP/IBP)
• Finance and accounting (budgets and cost controls)
• Marketing (consumer behavior, life cycle management, pricing)
• Operations and supply chain (resource planning, production, logistics, inventory)

Why Is Demand Planning Important?

In a world of increasing uncertainty, demand planning helps companies stay ahead. Done well, it enables organizations to:

• Improve service levels and customer satisfaction
• Minimize inventory carrying costs and waste
• Respond quickly to supply chain disruptions or market shifts
• Enhance collaboration between departments
• Increase profitability and operational efficiency

Demand planning is not a one-time task but an ongoing, iterative process that requires the correct data, tools, and cross-functional collaboration. It must also be flexible enough to adapt to volatility, whether driven by global events, consumer trends, or economic shifts.

Poor demand planning leads to the outcomes businesses aim to avoid: lost sales, excess inventory, wasted capital, and disconnected teams working from different assumptions. A well-executed demand planning process, on the other hand, builds organizational alignment, reduces bias, and leads to better business outcomes.

Why is it Critical for Businesses to Practice Demand Planning?

Demand planning is not just a supply chain function; it’s a core business process that drives strategic alignment, financial performance, and customer satisfaction. Based on IBF research from 34 organizations across different industries, companies that invest in structured, data-driven demand planning realize tangible benefits across key areas of the business.

1. Improve service and protect revenue: A strong demand planning process helps businesses meet customer needs with greater reliability, ensuring on-time and in-full (OTIF) performance, even in the face of market volatility or promotional spikes. The result? Improved customer satisfaction, stronger brand loyalty, and higher top-line revenue.

Fact: A 15-point improvement in forecast accuracy has been shown to drive on to two percent in top-line sales growth and improve OTIF performance, meaning fewer stockouts and more happy customers.

Demand planning ensures your business doesn’t miss out on sales because of poor availability. It provides the early visibility needed to make smarter inventory and production decisions, keeping your shelves stocked and your customers returning.

2. Increase operational efficiency and reduce cost: Demand planning enables organizations to run more efficiently by minimizing waste, improving resource utilization, and allowing smarter scheduling of production, logistics, and labor. It transforms decision-making from reactive to proactive—letting teams plan ahead rather than scramble in response.

Fact: A 15-point improvement in forecast accuracy can deliver a 2.3 percent or more increase in pre-tax net profit, driven by better operational alignment and cost control.

By aligning cross-functional teams around a consensus forecast, organizations reduce duplication of effort, optimize capacity, and ensure the right resources are available at the right time—leading to smoother operations and lower costs.

3. Manage assets and free up cash: Effective demand planning significantly improves companies’ inventory and working capital management. With clearer insight into what’s actually needed—and when—businesses can reduce excess inventory, lower carrying costs, and avoid the pitfalls of overproduction or fire-sale markdowns.

Fact: For every 15-point improvement in forecast accuracy, companies can realize a 12 percent reduction in inventory, freeing up valuable cash and minimizing waste.

Demand planning ensures businesses are not over-invested in supply, storage, staffing, or space. It helps unlock capital tied up in inventory and directs it toward more strategic, value-added investments.

Demand planning is no longer optional. It’s a strategic necessity. Organizations that invest in robust demand planning processes not only gain greater visibility and control but also position themselves to thrive in a constantly evolving marketplace. With the proper training, structure, and leadership, demand planning becomes a competitive advantage that enables more resilient, data-driven organizations.

Where Does Demand Planning Fit Within an Organization?

Demand planning is a strategic, cross-functional process that touches nearly every part of the organization—from supply chain and operations to sales, marketing, and finance. While its reporting structure can vary, what matters most is how the function is structured, supported, and empowered, not simply where it reports.

Based on IBF research and industry benchmarks:

• 48 percent of demand planning functions report into supply chain or operations
• 23 percent report into the commercial side of the business, such as sales or marketing
• 8 percent report into finance
• 10 percent operate as an independent function or report directly to a business unit owner
• The remaining 11 percent follow other models depending on organizational design.

These variations reflect the flexibility of demand planning—it can reside within different departments, depending on the company’s structure, maturity, and strategic priorities.

But here’s the key: regardless of the reporting line, demand planning must operate as a cross-functional, collaborative, and unbiased process. Its success depends on its ability to engage multiple stakeholders, reconcile competing priorities, and drive consensus to produce a unified, realistic view of future demand.

The Complexities of Demand Planning

Finding and maintaining the perfect balance between sufficiency and surplus can prove especially tricky. It isn’t a once-and-done task. Economic conditions change, and competitive environments constantly evolve.

To address this, demand planning typically requires using demand forecasting to predict future demand trends. This has added benefits, most importantly, heightened company efficiency and increased customer satisfaction.

What are the Key Components of Demand Planning?

Here are the critical parts of demand planning:

Product portfolio management

Effective demand management requires a clear understanding of product lifecycles, from launch to phase-out. Product portfolio management supports this by tracking each product’s stage and showing how changes in demand can impact related items. It also plays a key role in planning new product introductions, helping teams anticipate demand, allocate resources, and support successful launches. With strong portfolio management, companies can better manage transitions, reduce risk, and respond more effectively to market changes.

Statistical forecasting

Statistical forecasting is based on the concept that past history best predicts future performance. It uses complex algorithms to analyze historical data to develop demand forecasts. This exacting process demands accurate data, including eliminating outliers, exclusions, and baseless or inaccurate assumptions.

Sales forecast and overrides

As a process champion, the demand planner plays a critical role in driving consistency, structure, and accountability across the forecasting process. One of the key responsibilities is managing sales inputs and overrides—ensuring that adjustments to the statistical forecast are based on valid insights rather than bias. This involves working closely with sales teams to understand market intelligence, promotions, and customer expectations while also challenging assumptions when needed. The goal is to balance collaboration with discipline, ensuring that overrides improve forecast accuracy and align with broader business objectives.

Trade promotion management

In today’s highly competitive environment, it can be challenging to spark the interest of prospective customers. That’s why sales and other promotions are becoming increasingly common. They often result in increased consumer demand. Trade promotion management helps ensure that these types of programs are properly executed, that there is adequate product supply, and that they deliver all expected benefits to a company.

Demand Planning Methods

Quantitative forecasting methods are the foundation of most forecasting processes, with approximately 74 percent of companies relying on historical data to project future demand. Standard demand forecasting methods are:

• Time series models, used by nearly half of organizations (48 percent), are the most common approach and focus on identifying patterns, trends, and seasonality in historical data.
• Cause-and-effect models, used by 17 percent of companies, link external or internal variables—like price changes or promotions—to shifts in demand behavior.
• Machine learning and AI are emerging tools in forecasting. Currently, about six percent of organizations use them, and as adoption grows, they offer the potential for more adaptive and automated insights.
• Judgmental forecasting, reported by 17 percent of companies, is a qualitative method incorporating expert knowledge, market intelligence, and human insight when data is limited or context is needed.

What is Required to Do Demand Planning Effectively?

Effective demand planning is more than just generating a forecast. It’s about creating a reliable, unbiased view of future demand that drives smarter decisions across the organization. Done right, it improves service levels, optimizes inventory, enhances collaboration, and ultimately boosts profitability. However, to achieve these outcomes, companies must establish the proper foundation. Here’s what’s truly required to do demand planning effectively:

• A clearly defined process: An effective demand planning process must be structured, repeatable, and aligned with business goals. It should define all stakeholders’ roles, responsibilities, timelines, and expectations. The process should incorporate steps for data collection, model development, consensus building, evaluation, and communication—ensuring that each cycle produces more accurate and actionable insights than the last.
• High-quality, clean data: The best forecasts are built on relevant, clean, and complete data. That includes historical sales, customer orders, promotional activity, and external factors like market trends and economic indicators. Without trustworthy inputs, even the most sophisticated models will produce unreliable outputs. Demand planners must work with IT and business teams to ensure data integrity, consistency, and standardization.
• Forecasting approach: An effective demand planning process requires selecting the right forecasting approach, whether it’s bottom-up (built from item-level inputs), top-down (driven by high-level business targets), or middle-out (a blend of both, used to reconcile plans across levels). Planners must also determine the appropriate level of aggregation, such as by item, customer, location, or time, based on how the forecast will be used and the level of noise in the data. The planning horizon must match the decision being supported—ranging from strategic (long-term capacity and investments) to tactical (monthly or quarterly planning) to operational (weekly or daily execution). Since no forecast is perfectly accurate, planners should establish acceptable and expected error thresholds and measure forecast performance to continuously improve.
• Cross-functional collaboration: Demand planning is inherently cross-functional, involving input from sales, marketing, supply chain, finance, and operations. To be effective, the process must include a consensus step, where teams align on a final, agreed-upon forecast. This collaboration minimizes bias, integrates commercial intelligence, and ensures the forecast reflects both statistical outputs and business realities.
• Skilled demand planners: The demand planner plays a critical role as a process champion and cross-functional influencer. Strong planners possess analytical capabilities, organizational awareness, communication skills, and the ability to challenge assumptions objectively. They must manage statistical models, evaluate overrides, monitor forecast accuracy, and facilitate dialogue between departments.
• Focus on continuous improvement: No forecast will be perfect, but the goal is to improve continuously. That means measuring forecast accuracy and bias, tracking value-added steps, and adjusting models and inputs over time. Each forecasting cycle should yield better insights and inform more intelligent decisions.
• Executive support and integration into business strategy: Demand planning must be embedded in the organization’s decision-making processes with strong executive support to ensure it has the visibility, tools, and authority to drive change. Gaining buy-in from key stakeholders is equally critical, as it builds alignment, promotes cross-functional engagement, and reinforces the value demand planning brings through improved customer service, operational efficiency, and business performance.

Demand Planning: Best Practices

Once the foundational elements are in place, adopting these best practices ensures demand planning becomes a value-driving process that adapts to change and supports better business outcomes:

• Understand the purpose of forecasting: Clearly define why you are forecasting—whether for financial alignment, production planning, or service optimization—to tailor the process accordingly. Anchor the planning process in key business questions and explicitly state the assumptions driving forecast changes and decision-making.
• Identify demand drivers: Analyze internal and external factors—such as seasonality, promotions, economic trends, and customer behavior—that influence demand patterns.
• Gather relevant inputs across functions: Incorporate insights from sales, marketing, finance, and operations to ensure the forecast reflects a broad and informed perspective. Cleansing and structuring data is essential to ensure accuracy and consistency, providing a reliable foundation for effective forecasting and informed decision-making.
• Track forecast performance regularly: Measure and report forecast accuracy and bias at appropriate levels of aggregation to continuously improve planning effectiveness. Forecast errors and metrics help us identify uncertainty and bias, allowing us to communicate them clearly, prioritize errors in high-value products and items, and improve forecast accuracy through better inputs and process refinement.
• Schedule timely and recurring meetings: Regular forecast review meetings enable collaboration, resolve conflicts, and build consensus around the final demand plan. Demand planning should act as a hub for cross-functional alignment, bringing together departments to drive consensus and accountability.
• Communicate and manage results: Share insights and results across the organization, highlighting successes, identifying gaps, and reinforcing the value of the demand planning process.

What Skills Do Demand Planners Need?

Effective demand planners must combine analytical expertise with business acumen to interpret data and translate it into actionable insights. They need strong communication and collaboration skills to work cross-functionally with sales, marketing, finance, and operations, facilitating alignment and consensus. A deep understanding of forecasting techniques—from time series models to causal methods and emerging AI tools—is essential to building and evaluating accurate forecasts.

Demand planners must also be adept at managing uncertainty and bias, using metrics to identify errors, and continuously improving forecast performance. Critical thinking and problem-solving abilities are key to challenging assumptions, evaluating overrides, and navigating business complexity. Equally important is the ability to act as a process champion, ensuring the planning cycle is structured, repeatable, and aligned with strategic goals. Ultimately, demand planners serve as integrators across the organization, requiring a balance of technical skills, strategic thinking, and emotional intelligence to influence without authority.

The Future of Demand Planning

The future of demand planning is rapidly evolving into a more strategic, technology-enabled, and integrated function that drives value across the entire enterprise. Fueled by advancements in artificial intelligence (AI), machine learning, and predictive analytics, demand planning is becoming more precise, automated, and responsive. These technologies allow organizations to analyze vast amounts of real-time data from sources like point-of-sale systems, distributors, and suppliers, enabling more accurate forecasts and timely decisions that reduce waste and improve customer service.

As forecasting tools become more sophisticated, the demand planner’s role will shift from generating numbers to generating insights, focusing on scenario planning, cross-functional collaboration, and business alignment. Demand planning will continue to integrate with S&OP and IBP processes, connecting operational planning to financial and strategic goals. With global supply chains becoming more complex and volatile, demand planners will be expected to manage greater uncertainty while maintaining agility and discipline.

However, as Eric Wilson of the Institute of Business Forecasting (IBF) cautions, the successful integration of advanced technologies requires more than just investment—it demands alignment with business strategy, proper implementation, and upskilling teams to interpret and act on AI-driven insights. Without these, organizations risk underutilizing powerful tools or making misaligned decisions. Done right, the future of demand planning is not just digitality becoming a central pillar of strategy and competitive advantage.

Demand Planning 101: The Final Word

The world of demand planning is rapidly evolving. However, the reality is that companies that don’t practice it must jump on board. If they don’t, they risk losing out to competitors who do. Demand planning will help you satisfy consumers, run your organization efficiently, and drive dollars to your bottom line.

Leverage the information in this guide—and the other resources available through IBF—to launch and optimize a demand planning practice at your company.

Demand forecasting and demand planning are foundational elements of business plans and business strategies across the many functions within the company. They encompass long-term planning, short-term planning, and everything in between.

They are key factors in Marketing Planning, Sales Planning, Supply Chain Planning, Product Development Planning, Capital Investment Decisions, Operations Planning, Inventory Planning, Financial Planning, and other business planning. They are critical elements in the development of short-term and long-term business strategies for the company and its functional areas.

Demand Planning is More Than S&OP

Many of the business decisions made throughout the company depend upon the insights, knowledge, and proficiency of Demand Planners. Demand Planners must be concerned with the business behavior affecting business-to-business product and service transactions, and with the consumer behavior of the ultimate product and service users. Demand forecasting and planning are disciplines that are applied well beyond their uses in the S&OP/IBP processes for the company.

“The Demand Planner must understand not only the company, its products and its businesses, but the context in which the company is operating”

The Demand Planner must understand not only the company, its products, and its businesses, but the context in which the company is conducting its business. This requires curiosity, vision, analytical skills (both static and dynamic), multi-time horizon adaptability, and the ability to work with others cross-functionally and across management hierarchies.  Demand Planners are imbedded in functions all across the company within the many functional responsibility areas. While their functional locations may vary, their profession has common important elements and considerations that are fundamental to the work that they do. What are some of these elements?

What Separates Great Demand Planners from the Merely Good

1. Understanding of the relevant industry, industry segments, and associated trends and developments
   2. Knowledge of minor, major and emerging competitors and their strategies and activities
   3. An understanding of economic conditions and trends affecting the company and its products and services sales – both domestic and global
   4. An understanding of political conditions and trends – domestic and global – which are affecting the company and its products and services
   5. A knowledge of demographic changes and trends affecting consumer demand for its products
   6. A knowledge of the key drivers of customer demand behaviors and that of consumers for the company’s products and services
   7. An ability to use technology and data sources ( internal and external) creatively and effectively for developing demand models, as well as performing demand analytics and for short-term, medium-term, and long-term projections of demand for use in business decisions and plans
   8. A knowledge of historical patterns of demand and emerging changes that might fundamentally affect demand through time
   9. A well-developed ability to communicate clearly and effectively across functions and management levels
   10. An ability to cohesively link all of the above to company goals – financial and non-financial – and to describe and explore the related business ramifications of scenarios, risks, and opportunities.

“Demand Planners represent a delicate balance of quantitative and qualitative skills”

The above elements should be carefully considered during the recruiting and hiring process for Demand Forecasters and Planners. These elements should be considerations in making promotions and compensation decisions. Demand Planners are an important resource within the company, affecting many of its business decisions and business processes. Their functional placement will vary with company organization structure. But their needed skills and abilities are commonly shared regardless of their functional placement. Demand Planners represent a delicate balance of quantitative and qualitative skills and of business perspectives that help them in the forecasting, planning, and strategic undertakings across the company.

To get up to speed with the fundamentals of Demand Planning and Forecasting, join IBF for our 2- or 3-day Boot Camp in Chicago from March 13-15. You’ll receive training in best practices from leading experts, designed to improve supply chain and enterprise performance. Super Early Bird Pricing is open now. Details and registration.

Q. What is the best method to forecast in the toy industry ? Or any industry where 70% + of the portfolio is renewed every year across thousand of SKUs ? Aggregation is understood, problems starts when entering SKU territory .

A. There is no special model for the toy industry. There are three types of models: (1) Time Series, (2) Cause-and effect, and (3) Judgmental models. They apply to all industries. We use the model that best captures the data pattern. SKUs are always most difficult to forecast. Usually, we first make a forecast of the category, and then allocate the share of each SKU using the ratio of each SKU to the total based on the rolling average of the last 12 months or so. That is, what the ratio of SKU 1 is of the total category, what the ratio of SKU 2 is of the total category, and so on. By using these ratios, we can make a forecast of each SKU.

I hope this helps.

Happy forecasting!

Dr. Chaman L. Jain

Editor-in-Chief,

Journal of Business Forecasting

The planning community mourns the loss of one of its leading figures and most ardent champions. Alan Lee Milliken passed away on July 13 in Pensacola, FL.

Alan was a loving husband to his wife of 46 years, Elizabeth, and a proud father to two sons, Roger and Mark. For the team at IBF, he was a much respected colleague, trainer and educator. He shared his knowledge at countless IBF conferences over the course of two decades and guided multiple businesses across the globe to planning maturity through our consulting programs.

A native of Alabama, he graduated with a degree in Industrial Engineering from Auburn University, followed by an MBA at Clemson University, SC. In 1984 he started his career at chemicals giant BASF, where he would spend nearly four decades working in various supply chain and planning roles, only stepping down in 2019 to pursue his own supply chain consulting practice. In his latter years at BASF he led their internal supply chain planning education and development, sharing his wealth of experience to empower the next generation of planning leaders.

From those that knew him or saw him speak at a conference, his passion for teaching was clear. Giving back to the community – whether it was at BASF, an industry conference, or on an individual basis – was his north star in life. He was generous with his time and knowledge, always willing to discuss, engage and lend a hand. Modest and humble, he put himself out there not for the spotlight but to give back, personifying the IBF’s mission to Learn, Share, and Advance.

He was at the top of his field in terms of knowledge and expertise, for which he was recognized  by the IBF who awarded him the Excellence in Forecasting and Planning Award in 2013, and the Lifetime Achievement Award in 2019.

Alan (left) receiving IBF’s Excellence in Forecasting & Planning award in 2013.

Speaking of his contributions to the field, colleague and friend Patrick Bower said, “When Alan presented at conferences, he laced his deep knowledge with anecdotes, humor, folksy stories, and meaningful metaphors; literally helping thousands of people learn the profession. I would go out of my way to listen to Alan present to help me better articulate complex supply chain concepts.

He introduced me as the IBF’s Excellence in Forecasting winner in 2012, and I him in 2013. Prior to presenting each other, we chatted on the phone and talked about our lifework, what drove us and why we found the work interesting. He told me he felt a duty to give back to the profession as a way to pay forward those that helped him along the way.”  

Alan wrote extensively for the Journal of Business Forecasting, having written no less than a dozen articles from 2001 to 2023. The latest article appeared in our last special issue – the editorial team having reached out to him specifically to contribute his knowledge.

That article, about connecting supply chain planning to enterprise strategy, was classic Milliken, delving into both high level strategy and the nuances of operational planning that only somebody with four decades in the field could write. I encourage you to take a look at his body of work in the Journal.

Alan receiving IBF’s Lifetime Achievement award in 2019.

Speaking of his personal and professional relationship with Alan, Editor in Chief, Dr. Chaman Jain, had the following to say: “He was a great friend – very sincere, trustworthy and helpful. He possessed a vast knowledge of demand planning. Any time I had a question or wanted a different perspective, I would turn to Alan. He would always take the time to clarify something or share his thoughts. I am going to miss him.”

He was also a key contributor to the Fundamentals of Forecasting and Demand Planning, one of the seminal works in the demand planning field.

With his easy, southern style and warm demeanor, he was every inch the gentleman. In sharing his knowledge for the benefit of others, he was a tireless advocate for the supply chain discipline. For his students, he was a much-loved and inspirational mentor. He will be missed dearly. 

Thank you, Alan.

The IBF team.

Alan’s family has created this Life Tributes page where loved ones can share memories and express condolences. 

What is Business Forecasting?

Business forecasting is the process of using analytics and experience to make predictions about future customer/consumer demand. The goal is to go beyond knowing what has happened to arrive at the best assessment of what will happen in the future so a company can make optimal business decisions, whether that be operational or strategic. Business forecasting incorporates a lot of different data and viewpoints, uses forecasting tools for modelling, and generates numbers (forecasts) that be used in multiple areas of the business.

What is Demand Planning?

Demand planning is the process of identifying and managing customer/consumer demand for a company’s goods or services and formulating responses to meet that demand. The idea is to balance demand and supply, i.e. serving the customer with the products they want while optimizing the operational elements that go into it.

People use the terms ‘demand planning’ and ‘forecasting’ almost synonymously but there are some differences. Demand planning is the process that drives operational supply chain activities like resource planning, production, logistics, and inventory policies. Forecasting generates the numbers used to inform those activities.

Demand planning is typically manifest in cross-functional processes like Sales & Operations Planning (S&OP) or Integrated Business Planning (IBP) that bring different functions together to decide on what the company can deliver and manage the trade-offs between Production, Supply Chain, Finance, Sales & Marketing etc.

Whatever you call it, you’re trying to predict what a company will sell in the future to successfully be able to supply it when it’s needed.

What Happens When a Company Doesn’t Have Good Forecasts?

If you have bad demand forecasts you may make poor decisions. If you underestimate demand, it can result in lost sales or, even worse, lost customers. If you overestimate demand, it can mean wasting money on inventory you can’t sell and tying up capital that could be better utilized elsewhere.

With a good forecast you give the customer what they want, when they want it, thereby maximizing sales and helping deliver on the strategic goals of the company. With an idea of what’s going to happen before it occurs, you can set inventory policies, set production schedules, determine investments, predict market impacts, control costs, and understand the lifecycles of your products.

What are the Key Steps in Demand Planning?

Demand planning is about more than just a number – it’s a process with a lot of different elements.

Data Collection: Data can come from multiple sources. We must understand what exactly is out there as far as inputs and insights and know how we can bring those into the forecast. Data typically includes historical sales data and qualitative information from Sales about key customers and from Marketing who can reveal how promotional activity will impact demand.

Data Analysis: The data you get won’t always be clean and usable in its current format it will require some preparation before analysing it. We need to look for anomalies in the data as well as formatting issues, determine what data is relevant and what isn’t, and make sure we’re using the right amount of data.

Forecast modelling: Multiple time series methods can be used to take the data, extrapolate it forward, and arrive at a forecast. Increasingly companies are turning to advanced systems to do machine learning and AI which use a wider range of data and automate much of the process.

Gaining Consensus: A challenging part of the process for a lot of companies is arriving at one number used by the different functions. You need everyone on the same page in terms of what you think is going to happen in the future – and collaboration is fundamental to this. This where collaborative planning forums like S&OP and IBP come in.

Communicating the forecast assumptions: This is often overlooked. We need to explain the expected result (forecast) and the reasons behind as this is key to those forecasts being trusted and therefore used across the business.

What Data is Used in Business Forecasting?

It can be internal data such as sales orders, or external data which a lot of companies are starting to look at now. External data includes customer information, macro information, and demographic data, as well as causal information like sales promotions or weather data.

Data is either structured (easily managed in a spreadsheet and easily accessible) or unstructured (not easily managed in a spreadsheet and often difficult to access). Unstructured represents over 85 percent of the data out there and includes data from social media comments, product reviews, and audio and video content.

What Forecasting Models are Used in Business Forecasting?

There are a lot of different models available. This is because there’s a lot of different types of data out there which require different forecasting approaches. At one extreme we have pure qualitative and knowledge based judgements. This could be a sales team giving their own estimate of sales and then you’re aggregating those things up. At the other extreme you have pure quantitative approaches like machine learning with less human judgement and intervention.

In the middle there are various types of Time Series methodologies and causal models. There’s no right or wrong model or approach – rather we must choose the best approach for the data we have and the resources and time we have to generate a forecast. According to IBF research, right now most companies use Time Series types of data in their modelling and their preferred method is exponential smoothing. Does that mean exponential smoothing is the best? Not necessarily, but it is versatile method and it’s good for a lot of Time Series data.

What is Bias in Forecasting?

Bias is consistent over-or under-forecasting. It can be conscious or unconscious. For example, Sales may always forecast higher sales numbers because they want the inventory on hand in case they make the sale, or Finance may always push the number down to to avoid tying up cash in inventory. Whether it is high or low, bias is dangerous and gives a false picture of the future. It creates bad decisions and deteriorates the trust in the forecasting process. Bias is actually often worse than uncertainty.

To learn the fundamentals of business forecasting and demand planning, join us for IBF’s Chicago Demand Planning & Forecasting Boot Camp from March 15-17, 2023. You’ll learn how to forecast demand and balance demand and supply from world-leading experts. Click here for more information. 

You can’t turn on the TV, open your internet browser or read a business periodical without seeing something new about corporations missing their objectives due to supply chain disruptions and demand swings. The pandemic, inflation, and the war in Ukraine placed exponential variabilities on existing business processes that continue to get more and more complex with each passing year.

Many of these struggles are en­countered when there is no formal integration between mid- to long-term corporate planning and boots-on the-ground, tactical execution activities. Given the different inte­grated planning processes already utilized by companies, do we need another business process (and yet another acronym)? Like all complex and nuanced questions, the answer is “it depends”. If the organization currently has mid- to long-term stra­tegic plans aligned, integrated, and achieving their company objectives, the answer is a straightforward “no”.

For businesses struggling to achieve their goals during the last two years given the challenges described above, however, an additional formal practice to align their approaches to tackle these headwinds would be an enormous help.

The industry term for such a pro­cess is Sales & Operations Execu­tion (S&OE). Over the last few years, S&OE has been increasingly written and talked about in the planning community as it successfully ad­dresses the pain points most com­panies have been facing. At the same time, many business practitio­ners think this is another unneces­sary, consultant-derived acronym designed to sell consulting services.

As a non-consultant working in the trenches of planning, I ask such scep­tics to reflect on the current global factors weighing heavily on the oper­ational efficiency of companies such as Apple, Microsoft, Amazon, Tesla, and others. The problems these companies are experiencing are well documented and no doubt all too fa­miliar for anyone in a supply chain or planning role.

What are the Differences Between S&OP/IBP & S&OE?

The simple difference between them is that S&OP/IBP is the high-level, 3 to 18 months ‘planning stage’ for an enterprise, business unit, or product family. In contrast, S&OE is the ‘transactional stage’ running anywhere from a week to a few months.

S&OE is where sales orders are entered, product jobs are released, POs are created, and intercompany transfer orders are issued, among other things. For ERP specialists fa­miliar with MPS/MRP planning ho­rizon terminology, the S&OP/IBP planning covers the long-range Fluid stage back into the Slush period, and then S&OE is the Slush order creation period, moving into the Frozen seg­ment.

The goal of the S&OE processes is to assist in achieving organizational objectives and financial commit­ments. This is done by identifying variances as they begin to emerge and addressing them within the weekly short-term cycles, instead of waiting for the monthly planning meetings. These S&OE processes and their supporting performance measurements aim to deliver on the S&OP/IBP plan by identifying short-term gaps and deciding on methods to address them.

Gaps can include plan disruptions due to supplier shipping delays, customer demand spikes and troughs, production throughput shortages, system planning parameter errors, logistics barriers, and warehouse storage constraints, to mention just some of the more common ones that have arisen recently amid the pandemic. Many companies have weekly — or even daily — tactical department meetings. Still, these are usually not cross-functional nor are they formally communicated to strategic planning, thereby failing to manage unplanned disruptions.

This lack of alignment tends to cause the mid- to long-term strategy (S&OP/IBP) meetings to spend significant time focusing on short-term, tactical firefighting instead of the mid- to long-term planning requirements needed to get out of these types of situations.

I like to sum this up by telling colleagues: “It’s a challenge to plan your way out of tactical problems and harder to execute out of the planning ones.” This is because without the appropriate mid to long-term forecasts, capacity supply plans, and other strategic business planning elements in place, it’s difficult to have the required downstream inventory to support the organizational objectives. Due to this, both elements are required to have a competitive advantage within today’s dynamic environment.

How Does S&OE Integrate With S&OP/IBP? 

Let’s walk through an example and see how S&OE integrated within a mature S&OP/IBP process will drive enhanced responsiveness and value for an organization. Imagine you’re in a leadership role of a craft beer manufacturer in the current environment. In 2022, you’re facing cost increases and shortages of critical raw materials of CO2, glass bottles, and aluminium.

With a mature S&OE process in place, you will pick up supplier price increases and delivery delays upon the purchase order confirmation entries within the ERP system. Analytical reports from this confirmation data will quickly inform the different cross-functional teams of the risks to the S&OP/IBP and financial plans, and which ERP parameters need to be updated for major variances before the purchase orders are even received at your facility. Reports from the planning tool will quickly inform the different cross-functional teams of the risks to the S&OP/IBP and financial plans, and which ERP parameters need updating.

Proactive use of Pareto-based analysis tools allows you to prioritize items that need to be addressed first; if supplier costs increases, the S&OE can assess what price increase the market will stand, and in the case of longer than expected lead times, alternate suppliers can be sourced. The S&OE team will leave longer-term risks and opportunities and overall cost and lead-time reductions to the S&OP/ IBP team

Companies are Ripe for Change

As Albert Einstein said, “Insanity is doing the same thing over and over and expecting different results”. Experiences of global leaders confirm that getting people to change and adopt new ways of thinking is one of the biggest barriers for middle managers when rolling out or upgrading a new S&OP/IBP or S&OE process.

Most company cultures have been formed over decades, requiring major disruptive events or changes within the top-level management to realize significant shifts in behavior. The positive news for those companies interested in implementing these changes is that the current business environment, with its major disruptive events, has driven many executive teams to move away from the old-school, siloed mindset.

COVID has forced an appreciation for both tactical and mid- to long-term planning, making businesses ripe for adoption of new processes. To close, do not worry about the acronyms referred to in this article (there is no correlation between what you call your planning process and its success). Instead, focus on whether your company has a process that brings different functions together to help your organization leverage its competitive advantages within your industry.

This article originally appeared in the Fall 2022 issue of the Journal of Business Forecasting. To receive a print copy of the Journal every quarter, become an IBF member or subscribe. 

Retailers, consumer packaged goods manufacturers, and their suppliers are arguably having the toughest year in decades as they struggle to understand changing consumer behavior amid difficult macroeconomic context and rising inflation.

This struggle in the first half of 2022 has challenged profitability, ballooned undesired inventories, eroded pricing power, and left companies guessing what the right product mix. Longing for a lower inventory-to-sales ratio and higher profit margins, growth is illusive. In the retail sector, evidence of this challenge is highly visible.

The solution to this situation is twofold: First, sensing the optimal mix while leveraging processes like collaborative planning, forecasting and replenishment. And second, shaping demand by leveraging new technologies and algorithms with optimal pricing.

The Art & Science of Optimal Product Mix

Getting product mix right is both an art and a (data) science. The art element is an understanding of the drivers of consumer behavior. The science is the diverse data from online and offline sources including but not limited to discretionary and non-discretionary purchases, footfalls and clicks, reviews and ratings, and macro- and micro-economic indicators. This combination of art and science allows us to understand responses to demand variation and gives us the knowledge to develop a financially viable and consumer demand driven product mix.

Understand Demand Drivers

With so many macro- and micro-trends compounding on consumer behavior, getting educated on consumer behavior is extremely important. While it’s an art to understand the consumer, that understanding can become more illuminated with data. This art currently lies in the consumer insights function of the organization which is often invisible to the operations function.

Organizations can gain visibility into this end consumer behavior with a digitally enabled omnichannel ordering and fulfilment ecosystem. There are a multitude of variable factors that go into influencing the product mix that consumers desire and it is up to us to determine the demand drivers across channels, product attributes and consumer demographics. It is essential for the insights team to understand the variability of these strongly correlated influencing attributes to arrive at an optimal product mix that responds to consumer needs in the current economic climate.

Making Sure “The Price Is Right”

Pricing is a powerful tool for organizations to execute on their strengths in normal times and is critical during times of inflation. Optimal pricing requires a comprehensive understanding of the marketing/merchandising and business operations, clarity in contract management, and an understanding of the competitive landscape to setup and execute negotiation strategies.

1) Understand Cost-to-Serve

Senior Management must initiate and implement a coordinated organization-wide effort to understand the cost-to-serve and related attribute correlations for their business. Depending on organizational structure, different costing methods, and different levels of knowledge, it can be difficult for different functions to measure costs and align on optimal pricing. Bear in mind this alignment requires collaboration between Finance, Marketing/Sales, Manufacturing, Procurement, Distribution, and Logistics teams. A cross-functional team of cost-experts operating within S&OP or IBP  must educate each other internally on different costs and evaluate pricing models for different offerings.

2) Offer New Products at Different Price Points

Organizations must look for opportunities to create offerings at different price points with the agility to configure products according to demand. This ability to offer different price points requires physical agility in the supply chain network as well. This may require using different modes of global and regional transportation, different warehousing solutions (centralized or distributed), different manufacturing solutions (in-house, outsourcing, multi-sourcing). Having multiple options at different nodes in the supply chain network makes more products available to customers at different price points.

3) Develop Customer Value Profiles

Organizations must create customer value profiles and capture pricing and service sensitivity of customers when deciding on pricing changes. Depending on their financial situation and purchasing power, customers and consumers will absorb varying degrees of price variations and service quality. It is vital to classify customers and consumers according to the prices and service quality (as measured by KPIS) that they will tolerate.

4) Develop Negotiation Strategies

Organizations must adopt top-down negotiation strategies for customers and suppliers. Pricing, being a strategic lever, needs clear rules of negotiation approved by leadership. Organizations can benefit from developing a RACI (Responsible, Accountable, Consulted, Informed) matrix that defines roles and ways of working that support decision making for new pricing models and responses to changes in the market.

In Summary

Competing in this emerging century of disruption, uncertainty, and volatility is not for the timid. As companies continue their evolution from linear “chain” thinking to ecosystem supply “network” thinking, they will have to assess, adapt, and mature their business models and organizational structures.

This adaptation is critical to maintain a competitive product mix and pricing response to ever increasing global change. Implementing an Integrated Business Planning process, enabling the organization with advanced analytics and technologies, and leveraging collaboration across the ecosystem will drive actionable outcomes for  growth.