It’s time for biotech to plan with the same precision it uses to develop therapies. 

In today’s fast-evolving biotech landscape, scientific discovery is moving faster than ever. However, while R&D is accelerating, many biotech companies are still struggling with outdated planning practices, particularly in the clinical supply chain. Spreadsheets, fragmented systems, and isolated teams lead to inefficiencies that delay trials, waste resources, and limit scalability.  

It’s time for a new mindset: one that treats planning not as a back-office function, but as a strategic enabler. From clinical forecasting to supply chain execution, biotech companies need to adopt advanced planning tools and processes that are agile, integrated, and built for complexity. 

The Planning Gap in Biotech 

Most biotech firms are born as lean, science-driven organizations. Planning tends to happen in Excel or disconnected ERP systems. But as trials scale and global complexity grows, this approach breaks down:  

•  Clinical teams manually forecast patient visits without aligning them with supply plans.
• Regulatory requirements are tracked separately, which risks last-minute relabelling. 

The clinical supply chain operates reactively, which leads to overstocking, rushed shipments, and stockouts. 

At the same time, many biotech companies are intensely focused on day-to-day execution: running trials, hitting recruitment targets, meeting regulatory milestones. With so much effort going into operational delivery, planning often becomes reactive or overlooked altogether. But having a good process is what allows teams to step back and see the bigger picture and ultimately make smarter decisions. The result? Slowdowns, budget overruns, and missed milestones that frustrate teams and investors alike. 

Why ERP isn’t enough

ERP systems are essential for executing transactions, tracking inventory, managing purchase orders, and controlling batches. However, they are limited when it comes to forward-looking scenario planning, demand modeling, and what-if simulations. 

In the biotech industry, where patient enrolment can change quickly, regulatory rules vary by country, and product shelf life is crucial, static ERP planning is insufficient. 

Enter APS: advanced planning & scheduling for Biotech.  

APS tools are built to handle the complexity of modern clinical supply chains. They allow companies to: 

• Forecast demand based on real-time patient enrolment and trial protocols 
• Plan production and packaging based on visit schedules and regional requirements 
• Optimize inventory across global depots to avoid waste and delays. 
• Run scenarios for delays, shortages, or protocol changes 

APS becomes even more powerful when embedded in a connected platform like Anaplan. It links clinical, supply chain, and regulatory planning into a single source of truth. 

Scenario planning: the new Biotech superpower 

Scenario planning is essential for resilience, not just a nice-to-have. Biotech companies can use it to answer questions such as: 

• What would happen if recruitment in Europe were delayed by three months? 
• How would a new labelling requirement in Japan affect our packaging lead times? 
• Can we reallocate inventory if enrolment spikes in a specific region?” 

This proactive approach reduces risk, increases agility, and enables better decision-making at every level of the organization. 

However, scenario planning involves more than answering isolated questions. It’s about developing a structured capability to test assumptions, quantify risk, and proactively guide decisions. 

Most importantly, scenarios aren’t built once and forgotten; they evolve. Modern platforms allow users to update key drivers in real time and immediately see the impact of those changes on plans. This helps teams act with speed and confidence, even when things don’t go according to plan, which they often don’t. Scenario planning brings science and operations closer together. It helps biotech companies transition from gut-feel decisions to data-driven, cross-functional alignment. 

Conclusion: planning is a strategic advantage 

Biotech companies can no longer afford to treat planning as a secondary or separate function. With increasing pressure to deliver faster, expand globally, and maintain compliance, the clinical supply chain must become more efficient. 

Advanced planning tools, such as advanced planning software (APS), scenario modelling, and supply chain planning software, are not just for big pharma anymore. These tools are essential for helping biotech organizations confidently transition from the lab to launch. 

Are you ready to rethink your planning approach? Learn how the BioScale App can help your team scale smarter, adapt faster, and gain visibility into every part of the clinical supply chain. 

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Executive summary | Future-proofing pharmaceutical supply chains is critical in an increasingly complex and unpredictable business environment. While redesigning the asset footprint is often impractical due to high costs and stringent regulations, pharmaceutical companies can ensure their supply chain is future-ready by selecting a fit-for-purpose technique. This article explores three data-driven strategies of future-proofing supply chains in the pharmaceutical industry: scenario modelling, allocation optimization, and capacity expansion – along with illustrative examples based on real-life projects in the Life Science industry. 

This article was published in the Journal of Business Forecasting | Volume 44 | Issue 2 | Summer 2025.

The pharmaceutical industry plays a crucial role in healthcare, providing essential medications and treatments to patients globally. However, the pressure on pharmaceutical companies continues to mount as supply chains become more global and decentralized, the global population grows and ages, and chronic diseases become more prevalent. Supply chain future-proofing is therefore imperative for pharmaceutical companies.

Normally, part of supply chain future-proofing includes redesigning the asset footprint. In the pharmaceutical industry, however, the tremendous costs and stringent regulatory aspects involved in altering the asset footprint itself make such a move rather impractical. This does not mean that pharmaceutical supply chains need not undergo futureproof design: rather, it means that they require a customized approach by carefully selecting techniques and strategies appropriate for this booming and incredibly complex industry.

I identify three key strategies to future-proof supply chains in the pharmaceutical industry: scenario modelling, allocation optimization, and capacity expansion. For each strategy, we provide an illustrative example, based on recent projects we have done for our Life Science customers. 

…

Click here to continue reading the full article. 

Curious to explore possibilities for supply chain future–proofing in your organization? Reach out to one of our strategic scenario planning experts today!  

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In 2024, EyeOn obtained its initial ISO 27001 certification.  

“EyeOn supports businesses in mission-critical processes where sensitive and high-impact data plays a central role. In many cases, this data directly drives revenue and performance. With ISO 27001 certification, we are proud to be among the leaders in our field of supply chain planning & forecasting to achieve this certificate” – Jasper Fase, Chief Financial Officer EyeOn

ISO 27001 certification further strengthens EyeOn’s position within the broader business ecosystem. Increasingly, suppliers across the industry demand ISO 27001 compliance to ensure robust data protection throughout the entire value chain. By meeting this standard, EyeOn not only safeguards data but also facilitates efficient and secure collaboration with clients and partners. 

“Our commitment to security doesn’t stop with a certificate on the wall. Each year, EyeOn organizes a dedicated Security Awareness Week, where the team revisits key ISO 27001 principles and best practices. To maintain our high standards, we’ve also established a specialized internal team focused on continuously upholding and improving our information security framework.” – Jasper Fase, Chief Financial Officer EyeOn

What is ISO 27001? 

ISO 27001 is the leading international standard published by the International Organization for Standardization (ISO). It sets out the requirements for implementing a robust information security framework within an organization and is internationally recognized as the benchmark for best practice all around the world. Having this certification demonstrates our organization’s commitment to continual improvement, development, and protection of information, assets and sensitive data by implementing and maintaining appropriate risk assessments, policies and controls. More information via www.iso.org 

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This milestone was achieved through a productive collaboration with Blenddata, whose expertise was instrumental in navigating the complexities of the migration. With Databricks, EyeOn is set to future-proof its platform and its AI capabilities, joining a forward-thinking group of companies that recognize Databricks as a key enabler of innovation. 

About Blenddata

Blenddata is a forward-thinking data engineering agency that unlocks the power of data for enhanced decision-making and business performance. They connect and integrate diverse data sources to build scalable, future-proof platforms tailored to each client’s needs. Their expert data architects and engineers work closely with clients across sectors, delivering sustainable solutions that drive operational excellence and competitive advantage. Backed by strategic partnerships, Blenddata transforms data challenges into strategic assets.

About EyeOn

EyeOn is a planning and forecasting consultancy that transforms supply chain planning processes into strategic advantages. With over 25 years of experience and a team of specialists across 7 global offices, EyeOn leverages cutting-edge techniques and continuous research to drive impactful improvements for multinational clients. Their tailored solutions optimize forecasting, streamline supply chain design, and elevate operational efficiency, delivering sustainable growth and profitability. Passionate and innovative, EyeOn is your partner for planning excellence.

For more information, visit EyeOn (https://www.eyeonplanning.com/) and Blenddata (https://www.blenddata.nl) 

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Last week, the US President announced the imposition of new tariffs. The image of US president Trump holding a board announcing these tariffs has become iconic. Almost no country and industry are unaffected by this move. Despite the uncertainty, business leaders must act decisively. The quicker and more effectively they respond, the more likely they are to secure a competitive advantage. EyeOn and Caroz are combining their expertise to ensure a swift response and effective realization. Here’s how we do it:

Optimize – network fast scan for insights

The primary short-term action is to reroute your supplies, optimizing the use of available assets and capacity in light of the newly imposed trade tariffs. As goods are rerouted, having up-to-date information on availability and transport rates is crucial to optimize your planning. Caroz, a leading 4PL and control tower provider, offers valuable insights into the transportation market, including the availability of lanes and transportation tariffs, assisting businesses in making informed decisions. This data from Caroz, along with trade tariff details, known supply capacities, and production costs, are integrated into the state-of-the-art supply chain network models of EyeOn. This integration facilitates the optimization of flows and enhances performance scenario analysis. 

In a network fast scan, we can offer you results to make informed decisions in days or weeks, rather than weeks or months. 

Analyze – adjust to latest

Developments are moving quickly, and the status quo is constantly evolving. Trade tariffs are under negotiation, while affected countries are considering retaliatory measures. This dynamic environment necessitates the ability to regularly review and revise decisions. As part of the EyeOn Planning Services we offer to maintain the network model in a live state, readily available for use. When needed, we update it with the latest volume information, transportation rates, and trade tariffs, and we assess the robustness of your strategic choices. 

Rerouting of flows focuses on optimizing what can be achieved within the existing infrastructure. However, in the longer run, infrastructure should not be considered a fixed asset. Factories can be relocated to geographies that are attractive not only from a trade tariff standpoint but also in terms of labor, transportation costs, and environmental aspects. This is an enhancement we offer; EyeOn and Caroz together handle the heavy lifting, allowing you, as a supply chain or business leader, to focus on making strategic decisions.

Operationalize – implement to change

To realize the benefits, one must, of course, implement them. This might sound trivial, but in these uncertain times, it places additional pressure on both the transportation and planning teams. Caroz and EyeOn can assist by integrating Caroz’s control towers for logistical execution with EyeOn’s planning services team. 

Caroz’s control tower can manage procurement, carrier performance, and order management, and even handle financial transactions. The outsourced planning team at EyeOn can take charge of demand and inventory planning. 

This arrangement can relieve your planning teams, ensure better performance, and allow supply chain and business leaders to focus on decision-making. With all the ongoing dynamics, there is a lot to manage, and it isn’t likely to be resolved soon. 

Want to effectively respond to trade tariffs? 

Contact us today, and within a week we will have: 

• Established a Non-Disclosure Agreement (NDA) 
• Organized a kick-off call to understand your specific needs 
• Shared the data templates for data collection 
• Agreed on a project timeline 

From there, we will focus on realization by ensuring the accuracy and timeliness of data, configuring the model for optimization, visualizing the results, and guiding you through the process and make it worry-free. 

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In our previous blog, we took a closer look at why traditional sales and operations planning (S&OP) processes often fall short for discrete manufacturers with complex engineering requirements. These manufacturers face unique challenges, such as managing the dynamic nature of projects with highly customized components, navigating frequent design changes, managing fluctuating resource demands, and coordinating complex bills of materials (BOMs). These factors create a level of complexity that traditional S&OP systems, with their rigidity and limited flexibility, are ill-equipped to handle. As a result, organizations often experience mismatched schedules, ineffective capacity management, cash flow disruptions and delays that undermine project timelines and overall efficiency. In this blog, we’ll explore a more adaptive approach to S&OP that is specifically designed to address these real-world challenges. By rethinking traditional processes and integrating tools and strategies such as scenario planning, real-time collaboration and dynamic capacity management, manufacturers can transform S&OP into a robust framework that not only meets the demands of complex engineering projects but also drives operational excellence. Read on to discover how this approach can streamline workflows, increase project visibility and control, and ultimately improve profitability while ensuring smoother project execution across your organization. 

How can companies improve this? 

While S&OP has proven to be effective across multiple industries, discrete manufacturing presents a unique set of challenges that highlight its limitations. Addressing these complexities requires rethinking traditional S&OP processes and adopting targeted strategies tailored to the dynamic demands of discrete manufacturing. Here are four key strategies to consider: 

1. Scenario planning:
   Scenario planning is a fundamental tool for managing uncertainty. By simulating project delays and assessing their financial impact, companies can proactively prepare for potential disruptions. This strategy enables manufacturers to anticipate delays in real time, adjust production schedules and quickly reallocate resources to minimize costs and maintain operations. Being prepared for the unexpected keeps companies agile and better equipped to meet challenges. 
2. Optimize planning parameters:
   Fine-tuning critical planning parameters is essential to aligning S&OP with the realities of discrete manufacturing. Refining variables such as lead times; inventory levels and capacity ensures that forecasts remain accurate and responsive to changing production demands. This continuous optimization minimizes excess inventory, increases production agility and enables companies to quickly adapt to changing market conditions. 
3. Improved BOM forecasting:
   Sophisticated forecasting configurations for BOM planning can transform production planning. Methods such as driver-based forecasting use historical data and customer trends to predict which configurations are likely to be in demand. This insight enables manufacturers to produce the right mix of components, reducing excess inventory, minimizing waste and improving overall efficiency. 
4. Sales funnel forecasting:
   Using real-time sales pipeline data to forecast demand bridges the gap between sales and production. Predicting demand based on current sales activity ensures that resources are allocated to meet expected demand, aligning production with market demand. This approach increases responsiveness, improves customer satisfaction and maximizes revenue potential by focusing resources where they’re needed most. Together, these strategies provide a comprehensive framework for modernizing S&OP in discrete manufacturing. By incorporating scenario planning, optimizing planning parameters, refining BOM forecasting and integrating sales funnel insights, companies can transform their S&OP processes to achieve greater accuracy, flexibility and profitability in an ever-changing landscape. 

How can tools support this? 

Advanced planning tools are essential for driving S&OP improvements, equipping companies with the technology to increase accuracy, efficiency, and responsiveness. In this blog, we highlight Anaplan and Jedox as examples of platforms that address the complex needs of discrete manufacturing. 

With Anaplan, manufacturers can integrate every aspect of their supply chain into a single, dynamic platform. Its real-time data visibility enables companies to respond quickly to market fluctuations and make informed decisions. Similarly, Jedox provides robust solutions tailored for manufacturers looking to customize their S&OP processes to better meet their unique challenges. Both tools bring flexibility and actionable insight to the planning process, enabling more accurate and agile decision making. 

Simulation and scenario planning tools
Simulation and scenario planning are among the most powerful features offered by these platforms. Anaplan, for example, allows companies to design and customize scenario planning to meet their
specific needs. Companies can simulate project delays, demand fluctuations, and rough-cut capacity planning (RCCP) and evaluate the financial and operational impact of each scenario. With this functionality, manufacturers can visualize how changes will affect cash flow and resource allocation – all within the same integrated tool. 

Optimizing planning parameters
Both Anaplan and Jedox excel at helping manufacturers optimize planning parameters. These tools allow users to automatically adjust critical variables such as lead times, inventory levels, and production capacity based on real-time data. They also provide customizable alerts and KPIs to ensure that production remains agile and aligned with changing demand and resource availability. By reducing excess inventory and improving working capital utilization, these platforms drive operational efficiencies and cost savings. 

Forecasting configurations with data-driven insights
When it comes to forecasting, Anaplan and Jedox use driver-based forecasting tools to predict which product configurations are most likely to be ordered by customers. These forecasts can incorporate data from external sources such as Dataiku, allowing companies to combine historical data with sales trends for more accurate predictions. This ensures that production schedules are closely aligned with customer demand, minimizing waste and maximizing production efficiency. 

Sales funnel forecasting
Both Anaplan and Jedox integrate real-time sales funnel data into their planning models. This sales funnel forecasting capability ensures that production and inventory levels are aligned with projected demand from the sales pipeline, improving responsiveness to market needs. 

By combining these advanced capabilities, Anaplan and Jedox provide manufacturers with a comprehensive toolkit for modernizing S&OP processes. These platforms enable dynamic, data-driven decision making that drives accuracy, flexibility, and profitability across the organization. 

Experiences and the implementation process 

Thales is a French multinational industrial group specializing in the design and manufacture of electrical systems for the aerospace, defence, transportation, and security industries was facing a sharp increase in demand that was outpacing its engineering and production capacity. This challenge was compounded by extended lead times for sourced parts, a siloed operational structure, and a lack of integrated tools linking engineering and production. These issues led to inefficiencies, fragmented efforts, and a lack of confidence in production planning data. 

To overcome these hurdles and prepare for future growth, the company partnered with EyeOn to implement a solution that would address its operational complexities while balancing project and product requirements. EyeOn facilitated seamless integration across functions by conducting data validation, stakeholder workshops, and thorough platform testing to ensure visibility and scalability. The company adopted Anaplan as its unified platform, enabling all Dutch business units to work from a single, transparent plan. This transformation enabled the organization to make data-driven decisions, improve resource management, and facilitate scenario planning. The implementation also increased executive engagement, operational agility, and cross-functional collaboration.  

Ready to transform your S&OP process and take control of your project timelines and cash flow? Download our interactive infographic to discover how a new approach to S&OP can help you overcome these challenges and drive sustainable growth. 

The post S&OP is broken in discrete manufacturing: can it be fixed? appeared first on EyeOn.

Sales & Operations Planning (S&OP) is intended to be the cornerstone of efficient business operations, helping align supply and demand while providing a clear roadmap for decision-making. Yet, in discrete manufacturing—where engineering plays a crucial role, such as in project businesses, defense, aerospace, and complex machinery—S&OP often fails to live up to its potential. The complexities of intricate Bills of Materials (BOMs), limited visibility into cash conversion cycles, and fragmented data undermine the effectiveness of traditional S&OP. 

Inaccurate cashflow forecasting 

In industries with long cash conversion cycles, like aerospace and defense and machinery, payments are often tied to project milestones, extending DSO (Days Sales Outstanding) significantly. For companies like Boeing and General Dynamics, it can take 12 to 24 months, or longer, to fully convert investments into cash. The frequent project delays and design changes disrupt production timelines, leaving components sitting in inventory and resulting in unreliable cash flow forecasts. 

This is where S&OP should act as the backbone of financial planning, but many companies fail to integrate lessons from previous projects, leading to overly optimistic and inaccurate forecasts.” 

Dealing with complex bill of materials 

Manage their complex Bills of Materials (BOMs) is critical in discrete engineering, as these BOMs often involve thousands of parts from multiple suppliers. Minor design changes can ripple through the supply chain, delaying production and escalating costs. Frequent updates, whether due to engineering revisions or customer demands, make it difficult to maintain timelines. 

Decoupling the engineering BOM from the Planning BOM can help solve this issue. A Planning BOM focuses on critical materials that have unpredictable demand or long lead times, enabling companies to forecast more accurately and avoid premature procurement.” 

Despite these strategies, many companies lack the necessary data and tools to manage BOM processes effectively. This often leads to imbalances in inventory, increased excess and obsolete (E&O) stock, and supplier disruptions. 

Inability to properly plan critical resources 

Furthermore, a common struggle is the challenge of planning critical resources due to fragmented data and poor visibility across departments. This misalignment between engineering, production, and supply chain teams leads to inefficient resource allocation. Additionally, a lack of robust scenario planning tools prevents companies from anticipating risks like supply chain disruptions or changing demand. As a result, companies often respond reactively, leading to higher costs and delays. They also fail to learn from past projects, repeating the same mistakes and neglecting the need to plan for specialized skills, which creates bottlenecks during critical stages. 

Why a new S&OP approach is needed 

To regain control over project timelines and working capital, discrete manufacturers need an S&OP process tailored to their specific challenges. A more agile, scenario-based approach is essential for navigating the complexities of discrete manufacturing. By integrating financial planning with project milestones and leveraging advanced forecasting tools, companies can better manage both operational and financial risks. This approach provides greater flexibility, helping to optimize capacity, address engineering delays, and improve cash flow forecasts. 

Ready to transform your S&OP process and take control of your project timelines and cash flow? Download our interactive infographic to discover how a new approach to S&OP can help you overcome these challenges and drive sustainable growth. 

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Executive summary – Despite increasing pressure to reduce working capital across many industries, many multinationals still set their safety stock targets as a number of weeks of demand depending on an item’s ABC/XYZ-segment, ignoring important aspects like lead time and replenishment quantities. This leaves room for improving costs, customer service and working capital. This article explains how to set up ABC/XYZ-segmentation in the right way and how to successfully implement inventory policies and service level differentiation in your organization. A real-life case study of a manufacturer of cargo securing systems is used to highlight best practices and the benefits gained.

This article was published in the Journal of Business Forecasting | Summer 2024.

Efficient inventory management is crucial for any business. While inventory is needed to meet customer service levels, optimize operations and mitigate uncertainties, organizations often struggle to balance customer service levels, inventory costs, and cash tied up in inventory. This challenge becomes even more complex when dealing with a broad portfolio of items with tens or even hundreds of thousands of items. Defining the inventory policy, target service level and replenishment parameters like safety stock or reorder point on an item-by-item basis is a paramount yet time-consuming task. In this article we explain how we have successfully applied inventory policy and service level differentiation techniques, and how to avoid common mistakes.

The value-add of inventory policy & service level differentiation

Striking the optimal balance between costs, customer service and cash is a complex matter. If all cost factors are known and customer service can be expressed in, for example, backorder or penalty costs, newsvendor equations can be used to find the optimal inventory targets (and ROI) per item and hence there is no need for segmentation. The reality is complicated though, as often not all cost parameters are known. Segmentation is a powerful tool to group items with similar characteristics and apply the same inventory policy and service level target, rather than having to manage every item individually. The key challenge is to find a segmentation approach that is simple enough to manage while optimizing the performance of a given group of items.

Why traditional ABC/XYZ segmentation often fails for safety stock management

Click here to continue reading the full article.

Curious to explore possibilities for ABC/XYZ segementation in your organization? Reach out to one of our inventory experts today!  

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Across industries, supply chain leaders will be replacing, upgrading, or expanding the capabilities of their advanced supply chain planning systems (APS) in the coming years to achieve their digital transformation goals and boost performance.  

Implementing advanced supply chain planning systems requires a thoughtful and systematic approach that ensures alignment with business objectives, seamless integration with planning processes, a robust and integrated functional solution across the IT landscape, and smooth adoption by the organization. 

In this blog, we dive deeper into what drives this steady increase in the implementation of advanced planning systems’ capabilities. On top of that, we also share the 5-phase digital transformation framework towards creating sustainable value from your next APS implementation.

Global disruptions as a new norm

Market dynamics and market complexity are at an all-time high. You can hardly speak of impactful supply chain events anymore, as global disruptions are no longer the exception, but the new norm. Many companies have experienced in recent years that they lack the digital planning capabilities to meet their needs for supply chain visibility, planning agility, scenario planning, and speed of decision-making.  
 
Companies are increasingly looking for ways to improve the efficiency of their planning process, automate repetitive planning tasks, and optimize network capacity and inventory. Building on a solid operating model, advanced supply chain planning tools provide the technical capabilities to achieve these goals. 
 
The pace of technological advancement and tool stack evolution (e.g., the retirement of SAP APO) is forcing companies to rethink their future digital strategy. There are many options to choose from, and companies need to decide which APS strategy best fits their longer-term needs and priorities.

Advanced supply chain planning systems implementation: focus on business and design

While the benefits of advanced planning systems’ capabilities are clear, the path to realization is not always that clearly defined.  

In our experience, companies fail to realize the full value of an implementation because they focus too much on the technical solution and not enough on business readiness, functional and applied design expertise, and a robust APS capability and support model. In addition, an advanced supply chain planning systems implementation requires focus, and investment in creating the optimal mix of process excellence, They start their advanced planning system digital transformation with a focused (re)definition of the supply chain operating model, which is then translated into a well-standardized process and organizational blueprint prior to vendor selection. 

1. Transformation plan & blueprint 

They start their advanced planning system digital transformation with a focused (re)definition of the supply chain operating model, which is then translated into a well-standardized process and organizational blueprint prior to vendor selection.  

2. Tool selection 

They ensure that user requirements are clearly defined and unambiguous, and they identify unique and high-value use cases that the tool should support as input to the vendor selection process. On top of that, they conduct a proof of concept or proof of value to assess the functional capabilities, intuitiveness, and performance of the solution(s) before making a final tool selection decision. 

3. Advanced planning systems readiness assessment 

They evaluate and make targeted investments in the supporting capabilities that will determine the system’s robustness and level of adoption. Specifically, they perform an early assessment of master data maturity and alignment of master data processes, governance, and support tools.  

Next, they make sure to assess and upgrade planner skills and enable timely change engagement. Finally, they define upfront what the future advanced planning system support model will look like and anticipate the required organizational changes. 

4. Advanced planning system design & solution development 

They ensure early vendor involvement in the functional design and solution design efforts. This is to gain a solid understanding of the functional coverage supported out-of-the-box versus the required customization (also considering the solution development roadmap). They apply an agile approach to configuration development with a good balance between core functionality, usability/user engagement, and performance.  

They make well-balanced decisions on the phasing of complexity, allowing for the adoption of baseline planning capabilities before introducing more advanced functionality. 

5. Go live, operationalization, and continuous improvement 

They allow for sufficient time during hypercare to transfer knowledge and skills from the central project team to local owners. A clear ownership and governance model for the different categories of support and continuous improvement (integration, performance, master data, functional enhancements) is in place.  

On top of that, they have dedicated specialist roles in place with clear ownership and resource allocation, because over time, an SME or key user model is not sufficient to drive structural standardization and continuous improvement of the solution. 

Ready to drive sustainable value from your next advanced supply chain planning system implementation?

Our extensive implementation experience has led to the creation of a proven framework that will help you become an advanced supply chain planning system champion and realize sustainable value. 

Our guide is your essential ingredient for APS success, helping you discover: 

• The essential role of APS in your digital transformation  
• The position of APS in your tooling landscape  
• The 5 key phases of a successful APS implementation 
• A proven checklist for each phase to get started immediately 

In this guide, we provide an end-to-end APS digital transformation framework and best-practice experiences to help you increase your chances of success and realize sustainable value. Download it here.   

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A few weeks ago, we had the opportunity to attend the International Symposium on Forecasting (ISF) in Dijon. It was great to engage with forecasting experts from industry and academia and to gain fresh perspectives on supply chain demand forecasting. One of the things that makes ISF stand out is its holistic approach to this topic. Yes, there is a significant focus on the technical aspects, such as new model architectures. But we all know that the forecast generated by a forecast engine is seldom the final forecast that ends up being used as input to make decisions within a business. Demand planners play an important role in enriching this “baseline” forecast by (if done well) adding information that was not captured in the model. This aspect was also given considerable attention at ISF – thanks among others to ongoing research by Robert Fildes and Paul Goodwin. 

At EyeOn we are also passionate about optimizing the demand planning process as a whole; making sure the overall process is efficient, and each component is adding value. In this blog, we will present our views on some effective best practices. 

Evaluating the quality of the entire demand planning process 

Most organizations measure the quality (i.e., forecast accuracy and bias) of the end result of the demand planning process; often referred to as the “final” or “consensus” forecast. However, these metrics alone don’t capture the value added throughout the process. For instance, you might be satisfied with an 80% forecast accuracy, but if the baseline forecast accuracy was 85%, you’ve invested valuable time and resources only to diminish the forecast quality. This example highlights the importance of tracking the Forecast Value Add (FVA) of enrichment: that is, to what extent are demand planners improving the baseline forecast. 

Monitoring only the FVA, however, isn’t enough. Imagine a scenario where the FVA is 10 percentage points, indicating that demand planners are excelling at improving the baseline forecast. Does this mean the overall demand planning process is flawless? Not necessarily. It might be that your forecast engine is underperforming; leading demand planners to spend considerable effort on enrichments that a higher-quality forecast engine could have handled more efficiently. In other words, if the forecasting engine were better, the planners wouldn’t need to spend as much time on adjustments. This example emphasizes the need to also evaluate the quality of your forecast engine by comparing it to a simple benchmark (e.g., by comparing the forecast accuracy of your forecast engine to a naïve forecast). In short, to assess the effectiveness of our overall demand planning process, we must evaluate the quality of all the individual components. 

But there’s more to consider 

While having these basic insights is a good starting point, they may not necessarily offer guidance on how to improve the quality of your enrichments. For this, you need to track details of the enrichment process, such as the number and type (e.g., direction, magnitude) of enrichments. This allows you to gain perspective on: 

• Which type of enrichments have historically been associated with positive/negative value add 

• Which parts of your product portfolio benefit most from demand planner interventions 
• The time invested in the enrichment process 
• Potential biases in enrichments

From insights to action 

Insights are valuable, but they should be in service of improving the process. Data-driven insights in the performance of the baseline forecast engine and the behavior of the demand planning team should provide concrete suggestions for process improvements, ultimately leading to: 

• Improved quality of enrichments, resulting in higher forecast value add and a better demand plan 
• Enhanced efficiency of your demand planning process through the adoption of a more targeted enrichment strategy
   

How EyeOn can support 

Making the value-add in forecasting tangible is at the core of what we do. And we offer multiple ways to get experience with it or even get started in a fast way.  

• Play our Forecast Game: a business game where you compete against others to create the best possible forecast, applying best-practice principles around forecast enrichments. Measuring and learning on forecast performance is at the heart of the game set-up.  

• Use our Smart-touch dashboard: a ready-to-use dashboard that provides all the insights discussed in this blog. Let’s connect your data and unlock direct insights to improve your forecasting and demand planning process.  

• Get your copy of our Statistical Forecasting e-book: ‘Statistical Forecasting as your steppingstone towards AI’. In the e-book, we explain how to set up statistical forecasting to create an optimal foundation for machine learning-based demand planning. Download it here. 

If you’d like to learn more, feel free to reach out to Rijk van der Meulen or Erik de Vos.

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