How CIOs Can Get Manufacturing Demand Planning Right

Straight line to results: Optimize demand planning to effectively meet rapidly evolving customer demand.

Analyst Perspective

Even before COVID-19 hit, the manufacturing industry had been contending with demand volatility. However, the pandemic highlighted the impact that external factors had on consumer demand: global supply chains stalled, a drastic reduction in the number of SKUs supplied by businesses, prolonged shortages of popular products, and a dramatic shift to online retail.

Conducting accurate demand forecasting and planning has never been an easy task. Effective demand planning has far-reaching consequences to your top-line and bottom-line by ensuring enough goods are produced and sold through the right channels, production planning is conducted in an optimum manner, the right level of inventory is maintained, and the total cost of supply chain ownership is low. There are several challenges businesses must overcome to get to the ideal operating state with demand planning. Legacy forecasting tools and Excel often cannot handle the amount of data required for an accurate plan, nor can they capture all available opportunities.

At the other end of the spectrum, traditional ERP systems do not provide planners with the flexibility they need to simulate options, test forecasting models, and adjudicate the accuracy of their demand planning logic. The answer to optimization challenges is a two-pronged approach; use a built-for-purpose demand planning system, and take a holistic view of your planning philosophy and performance management framework. In this research, we introduce the modern supply chain planning landscape, take a deep dive into demand management and its challenges, give you an overview of the ideal technology end state for demand planning, and introduce fit-for-purpose software. We then discuss some case studies spanning durable, non-durable, food and beverage, and chemical manufacturing industries to give you an idea of how other companies have approached the optimization of demand planning.

Shreyas Shukla

Principal Research Director, Manufacturing Industry

Info-Tech Research Group

Executive Summary

The most critical aspect of optimized demand planning is choosing a fit-for-purpose demand planning system which will provide a business with the capability and flexibility it needs to perform accurate demand planning.

How CIOs Can Get Demand Planning Right

Straight line to results: Optimize demand planning to effectively meet rapidly evolving customer demand.

EXECUTIVE BRIEF

COVID-19 made accurate demand planning extremely challenging

COVID-19 injected new complexities into the formal forecasting and planning processes. Businesses found that traditional forecasting and planning methods couldn’t keep up with constant market volatility. Demand cratered, then recovered, and reached unprecedented levels before entering the still-evolving soft downturn of early 2023.

New demand patterns emerged in 2020, forcing businesses to rethink their demand strategy.

Source: McKinsey, 2020

Businesses had to respond rapidly to a new kind of consumer

Disruptions during the pandemic, ongoing trade wars, geopolitical events, and rising inflation have resulted in a new global environment. Businesses have had to make a valiant effort to continue their manufacturing operations to stock shelves with product, while dealing with overtaxed and elongated supply chains.

Source: The New Consumer, 2023

The start of 2023 had some challenges in confidence

Businesses seem to be struggling with a large stockpile of inventory Companies may be forced to pause, delay or cancel orders, impacting supplier cash flow in favor of their own cashflow; this will negatively impact suppliers. There are indicators of a looming downturn led by a collapse in demand across the transport and logistics sector worldwide. While the economic environment has changed significantly since the pandemic began, 2023 is beginning to feel like a relapse of early 2020.

Quarter on quarter % growth of global transaction volumes

Source: Tradeshift, 2023

Year-over-year change in US consumer spending

Source: Earnest Analytics. 4-week trailing average, 2022

US Consumer Sentiment Index

Source: University of Michigan Surveys of Consumers, 2022

Change in US Consumer Price Index

Source: US Bureau of Labor Statistics, 2022

Transportation and manufacturing sectors are seeing a slowdown

Logistics managers are concerned for the future. The November 2022 Logistics Manager’s Index is at 53.6, the second lowest reading in its history. The lowest reading of 51.3 was from April 2020. This is due to low inventory levels, lower than expected manufacturing activity, expensive warehousing and a post-holiday spending lull with an expected downturn in 2023.

Transportation and logistics sector is firmly in slowdown territory. Overall warehouse capacity and transportation prices contracted considerably in 2022.

Manufacturing saw a slight improvement in Q4 2022 due to consistent easing of supply bottlenecks. The manufacturing sector, however, continues to remain in contraction territory due to waning demand after the holiday season, and careful spending by consumers due to fears of a looming recession.

Retail has been performing near expectation for the majority of 2022. The holiday season has been lucrative with month-on-month sales up by over 7% from November to December.

Technology Spending outperformed all other sectors in Q4, 2022 despite the hammering that tech stocks have received due to economic headwinds. Businesses continue to invest in digital transformation initiatives and worldwide IT spending is expected to grow by 5.1% in 2023.

Global quarter on quarter % growth of global transaction volumes by sector

“CEOs and boards tell me they are cautious, particularly in the near term. They're rethinking business opportunities and would like to see more stability before committing to longer-term plans. Many firms have started preparing for tougher times, focusing on factors within their control.”

- David Solomon, CEO, Goldman Sachs; quoted in Business Insider India, January 21, 2023.

Source: Tradeshift, 2023

Planning is the primary focus going forward.

Supply chain planning is the top priority for organizations in 2023 (Supply Chain Management Priorities and Challenges survey, APQC, 2023). Demand planning and forecasting is the top focus area within supply chain planning.

Continued disruptions and demand volatility mean that demand planning and forecasting will be a key competitive differentiator. From the start of the COVID-19 pandemic till now, most businesses feel that investing in better planning capabilities will ensure they meet and / or exceed their goals.

Source: APQC, 2023

Section 1

Introduction to demand planning and advanced planning concepts

Optimize demand planning to effectively meet rapidly evolving customer demand

Evolution of the supply chain planning landscape

The evolution of supply chain planning has been characterized by increasing integration of separate tasks. In the 90s, all planning elements of the supply chain became integrated under a single management perspective. In the 2000s, evolving IT and communication technologies allowed for a complete integration under the supply chain management function. Since the 2010s, the growing level of digitalization and automation has been a dominant element in the evolution of planning.

Source: SCM Dojo Blog, 2023

The modern supply chain planning landscape

Supply chain management deals with the complete flow of goods (and services) starting with the raw material and ending with the finished product in the hands of the customer. R.K. Oliver and M. Webber coined the term “supply chain management” in 1982.

Supply chain business planning is a critical building block of supply chain management. It cuts across long-term, mid-term and short-term time dimensions to incorporate preparation and execution steps for finished goods. Supply chain business planning covers several business domains and produces many outcomes:

Long-term business plans are created based on strategic planning decisions. These can cover 2- to 10-year periods. Long-term business plans help to establish objectives, policies, and the operating footprint of the supply chain.

Mid-term business plans are created based on tactical and some operational planning decisions. These typically cover 1 to 1.5-year periods but can range anywhere from 6 months to 2 years. They are updated on a rolling basis and deploy resources to match supply with demand.

Short-term business plans are created based on operational and execution planning decisions. These typically cover daily, weekly, monthly, and sometimes quarterly planning periods and are also updated on a rolling basis. Short-term plans are used to schedule, monitor, control, and adjust production activities as well as build, store, and transport finished product.

Source: European Journal of Operational Research, 2005

Implementing the 3 levels of supply chain planning

Effective implementation of the 3 levels of supply chain business planning is essential for optimum use of available resources and a profitable business. Each level has a distinct set of characteristics, activities, outcomes, priorities and challenges. These must be balanced to ensure goals and objectives are met.

Source: Quality Gurus, 2022

Bringing it all together from planning to execution

A typical supply chain plan involves complex relationships between components of the business planning layers. For successful execution on the shop floor, different stakeholders need to constantly communicate with each other. This relationship needs to run like a well-oiled machine.

Introduction to demand management

Demand management consists of two components: demand forecasting and demand planning. Demand management requires responding to or influencing the pattern or consistency of demand in line with organizational objectives. This involves forecasting unconstrained demand and subsequently layering it with operational details and constraints that a financial, market-related, supplier-related, operational, self-inflicted, and customer specific.

• Demand forecasting is the process of predicting future demand through analysis of historical facts and near real-time data. This is a simple prediction of future events to help calculate what product, and how much of it, customers will demand in the future.
• Demand planning is the “the management process within an organization which enables that organization to tailor its capacity … to meet variations in demand.” (The Chartered Institute of Procurement and Supply (CIPS)). Demand planning draws from and operationalizes the demand forecast by managing future demand to reach operational and financial goals of the organization.

- Charles W. Chase, SAS Institute

Demand management involves complex relationships between strategy and operations

Strategic demand management activities require implementation of specific operational processes through which daily activities will be executed and measured.

Source: ExploreSCM, originally adapted from “The Supply Chain Management Process,” The International Journal of Logistics Management, Vol. 12, No. 2 (2001).

Demand planning flow of activities

Chosen demand planning software should be able support these advanced concepts

Use integrated business planning to synchronize key decisions

Integrated business planning takes a holistic view of procurement, production, distribution and sales. IBP integrates strategic planning with shop-floor execution and enables executive level participation for impactful decision-making IBP is achieved by accurately anticipating the demand for finished goods and figuring out the financial, material, and logistical considerations of trying to meet this demand in line with strategic and executive objectives. IBP is at the intersection of several planning activities:

• Integrated business planning bridges the gap between strategic S&OP and execution by translating outcomes into financial, material and resource requirements.
• Sales and operations planning enables executive decision-making to achieve a profitable financial outcome.
• Demand planning projects future demand for a product and adjusts output to meet that demand.
• Inventory management maintains the right amount of inventory to meet demand by balancing investment constraints and logistics costs with goals and objectives of the company.
• Supply planning deals with availability of raw material, its distribution, manufacturing, production, and procurement in line with planned demand.
• Material requirements planning specifies what is needed, how much of it, and when it is needed, assuming no production constraints.
• Production planning is the process of creating a guide explaining the steps involved in the production of a product or service.

Source: QAD DynaSys, 2023

Use demand excellence to improve the quality of your outcomes

Demand excellence refers to a demand planning ecosystem that delivers quality plans through a holistic view of the people, processes, technology, data, and measurements involved. Demand excellence is supported by demand statistics, demand planning, and demand consensus as the core process areas.

• Demand statistics involves generating the best quality statistical forecast by using the right combination of models / algorithms, and measuring the statistical performance of applied portfolio of models.
• Demand planning involves generating the best quality demand plan using the right mix of inputs, planner judgement, production parameters, and other activities in the ecosystem.
• Demand consensus involves generating a one-number plan through consensus-based decision making across participating departments. Consensus aims for transparency of outcomes throughout the organization.

A one-number forecast creates alignment and ensures that the whole company works to the same set of assumptions (The Institute of Business Forecasting & Planning). In some cases, the one number could be a common range that serves as the objective for the organization.

Source: Spinnaker

Use CPFR to collaborate with your suppliers and distributors toward a common objective

Collaborative planning, forecasting and replenishment (CPFR) enables companies to work together with their trading partners to improve forecasts, reduce inventory and production costs, and increase sales and profit (The Institute of Business Forecasting & Planning). CPFR was a concept jointly developed by Warner – Lambert and Walmart in 1995 to ensure the right amount of Listerine was available on Walmart’s store shelves.

Benefits of CPFR

“From the time we started the collaboration process at Meijer until the time I left, we had reduced our total logistics cost by more than 50 percent.”

- Ed Nieuwenhuis, Supply Chain Manager, Meijer Stores: Supply Chain Digest, 2008.

Improve revenue through technology led demand sensing and shaping capabilities

Demand sensing is used to predict near-term demand using short-term or recent data. While demand planning is effective in the short to mid-term and forecasting for the mid to long-term, demand sensing is used to fill the gap for near-term demand prediction. This is especially effective in volatile markets where demand sensing can be employed to accurately predict what will happen in the immediate future using short-term trends.

Demand shaping uses incentives, substitutions and dynamic cost adjustments to influence near-term demand. Organizations will typically employ demand shaping to match demand with the planned or available supply of certain products. Most promotions are common examples of demand shaping efforts. Demand shaping has immediate impacts on top line and inventory levels.

Source: AI Multiple via LinkedIn

Optimized demand planning has been challenging to achieve

Demand planning has a variety of pain points and irritations across the people, process, technology, data and measurement dimensions. This is usually due to the overall strategy pursued by businesses toward solving these challenges, often by means of more system implementation. Some of the most common challenges are:

Pre-Pandemic	Pandemic	Post-Pandemic
Demand planning is treated as an admin task and not strategic to objectives. Forecasts are siloed, budget-limited or aggressively management-directed. Assumptions and techniques are not challenged. Choosing right forecasting models is a challenge. Phase ins / phase outs are not part of regular workflow. Planning teams are conservative and won’t experiment with more advanced models.	Supply chains became elongated and demand planning assumptions had to be updated to account for this phenomenon. Availability of stock was a challenge and companies became aggressive procuring / scaling up production. Performance measures were abandoned in favor of aggressive procurement strategies. There was a rush toward system implementation, and options chosen were not necessarily best-fit.	Spending is trending downward, and customers have become price-sensitive. Businesses today have too much dead stock and scaled up production during the pandemic too rapidly. This is eating into margins. Finding experienced and skilled planning talent is challenging. Bias and accuracy continue to be critical areas of focus. Widespread use of Excel sheets or inflexible stand-in systems (like ERP) have been a roadblock to planning optimization.

Source: Contributor interviews, 2023

Section 2

Contrasting forecasting with planning and introduction to modeling methods.

Optimize demand planning to effectively meet rapidly evolving customer demand

“Demand forecasting” and “demand planning” are often used interchangeably

It is important to understand the differences between the two, and the techniques and methods employed for forecasting and planning.

Objectives of demand forecasting

1. Understand organizational objectives.
2. Continuously collect and analyze new information.
3. Estimate future events and provide a broad framework for planning based on assumptions.
4. Identify cause and effect of performance.
5. Communicate with stakeholders and obtain feedback continuously.
6. Focal point of forecasting is facts and sources of objective, quantitative information.

“Forecasting is a systematic attempt to probing the future through inference from facts that are already known”

- Louis Allen, Author, The Management Profession: Management Study Guide.

Objectives of demand planning

1. Define strategies to achieve organizational objectives within parameters defined by forecasting.
2. Define clear operational objectives and key results expected.
3. Identify, analyze, and communicate challenges or obstacles to achieve organizational objectives.
4. Develop performance tracking processes in line with defined key results per area.
5. Execute all steps as per plan.
6. Focal points are facts and expected results.

“Planning is deciding in advance what to do, how to do and who is to do it. Planning bridges the gap between where we are, to where we want to go.”

- Harold Koontz and Cyril O'Donnell, Authors, Principles of Management

Source: Management Study Guide, 2022

Demand planning software should enable a spectrum of methods

The portfolio of models applicable to a specific organization could be any combination of pure qualitative methods and pure quantitative methods. Depending on the organization, planning teams and overall objectives, there are cases where machine learning is required and others where planners’ judgement is key.

Source: Institute of Business Forecasting & Planning, 2017

Section 3

Measuring performance using KPIs

Optimize demand planning to effectively meet rapidly evolving customer demand

Demand planning KPIs provide critical intelligence

Successful demand planning requires continuous performance monitoring through specific key performance indicators. These KPIs will provide intelligence on critical processes and outcomes. KPIs help gauge results of the planning effort, provide insights about customers and demand, review ordering metrics, locate errors, and understand how sales predictions are resulting in performance on the ground. This information is critical to the bottom line.

Source: Oracle NetSuite, 2021

Demand planning software should report on essential KPIs at a minimum

Source: Oracle NetSuite, 2021

Section 4

Demand planning software, key features, and integration requirements

Optimize demand planning to effectively meet rapidly evolving customer demand

This is what an optimized demand planning technology ecosystem looks like

Current state

• Forecasts are imposed top-down and not discussed / challenged.
• There is little / no knowledge of forecasting models.
• Product lifecycle is not incorporated into the planning process.
• Little / no analysis or understanding of what changed between forecast and actuals.
• Little / no formal planning technology roadmap and business priorities are not considered.
• Tools are Excel-based and not integrated with upstream / downstream systems.
• Planning data management is manual, with many versions of critical data.
• Little / no formal planning performance monitoring or analysis. Reporting is manual and ad-hoc.

Optimized technology end state

• Formal technology roadmap exists, with business requirements and priorities incorporated.
• Clear visibility into plans and performance metrics across management hierarchies.
• Ability to apply several models, simulate results, and reduce expected error.
• Product lifecycle activities integrated into the planning process with clear tracking of outcomes and owners.
• Well integrated SAAS / PAAS products employed with user training and user manuals.
• Master data is centrally managed, access is controlled, and single source of truth clearly defined.

Pick a planning solution that enables improved outcomes

Each maturity level builds on the previous by enablement of new capabilities through advanced solutions and embedded artificial intelligence. This results in improved planner productivity, optimized process, and organizational visibility.

Source: Supply Chain Digest, 2020

Demand planning software and overview of core features and capabilities

Source: ScienceSoft, 2023

Demand planning software will need to integrate with other critical applications

Comparison of prominent options in the demand planning software space

Source: SoftwareReviews, 2023

Implementing demand planning software is a complex exercise

It is important for CIOs to track the return on investment (ROI) for an undertaking of this size and complexity. While successful planning is highly planner-dependent, implementing planning software and ensuring its integration with other critical applications is not an easy task.

Section 5

Differences in demand planning by industry and deep dive into case studies

Optimize demand planning to effectively meet rapidly evolving customer demand

Industries use different supply chain models for competitive differentiation

There are six distinct supply chain models. Though the components of the supply chain do not vary greatly between industries, the way they work and the outcomes they achieve vary.

Source: Institute for Defense & Business, 2021

Demand planning complexity varies across industries

This analysis is modeled on the profile and product portfolio of the Fortune 1000 companies. However, the patterns start blurring once small and medium enterprises and companies headquartered in other countries are added to the analysis.

Demand planning complexity originates from the following attributes.

A high complexity pattern has:

1. High demand variability
2. High product variety
3. High product lifecycle
4. High degree of seasonality
5. High number of product alternatives

Patterns representative of some of the largest players in each of these industries are illustrated on this page.

Case Study

How Danone fulfills its growth objectives with optimized end-to-end supply chain planning capabilities.

INDUSTRY: Food and Beverage

SOURCE: o9 Solutions, Inc.

Case Study

How Lush Cosmetics capitalized on a growing, competitive market with enhanced planning and reporting.

INDUSTRY: Non-durable Goods

SOURCE: Arkieva

Case Study

How ZF Friedrichshafen is driving the future of the automotive industry with enhanced demand planning.

INDUSTRY: Durable Goods

SOURCE: SAP

Case Study

How MilliporeSigma discovered the solution for high inventory levels and inaccurate forecasts through replenishment planning .

INDUSTRY: Chemical Mfg.

SOURCE: Logility

Case Study

How iNova improved planner productivity by replacing their Excel spreadsheets.

INDUSTRY: Pharmaceuticals

SOURCE: Logility

Next steps

1. Demand Planning Technology Maturity Model

   • Review the current state of your technology maturity using the attached framework.
   • Plan and prioritize initiatives in accordance with your current maturity, with the aim of reaching an optimized technology end state.
   • Download the model.

2. Review related research

   

3. Speak with an industry analyst

   • Book an analyst call and discuss your current challenges, transformation questions and latest trends
   Contact Us

Research Contributors & Experts

Arjit Saran

Demand Planning Lead

Signify

Anonymous

Professor, Supply Chain Management

American University

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