Pharmaceutical supply chain transformation

The pharmaceutical retail supply chain operates in a highly dynamic context, marked by strong pressure to ensure continuous availability, manage seasonality, and respond quickly to demand fluctuations.

In a context characterized by high demand variability, multiple stakeholders, and interdependent processes, obtaining an integrated view of supply chain operations is essential to identify constraints, inefficiencies, and opportunities for improvement.

The company and its purpose

The company in question has over 130 years of experience and serves approximately one billion consumers globally. With a strong presence in Australia, particularly in Melbourne and Sydney, its purpose is to ensure safe and effective daily care at every stage of people’s lives, always putting people first.

The organization believes that when consumers can rely on consistent, high-quality care, they become healthier and more empowered to fully engage with the world around them. This responsibility is reflected in operations guided by integrity, science, and quality.

Science is therefore at the core of how the company develops and delivers solutions for everyday needs, maintaining a continuous focus on innovation, product effectiveness, and sustainable value creation. At the same time, it promotes an inclusive and collaborative culture in which strong teams drive strong brands and deliver consistent results.

Figure 1 – Company core values

Project context and framework

In the Asia-Pacific market, the organization faced significant challenges throughout the supply chain, from the distribution center to product availability on retail shelves. Despite high levels of team commitment and collaborative relationships among the different stakeholders, there were frequent stockouts, misaligned inventory, and lower-than-expected service levels.

Rapid business growth, combined with poorly standardized processes, misaligned forecasting models, and high demand variability, was generating:

• Low on-shelf availability for certain critical SKUs.
• Excess inventory at certain points in the chain and shortages at others.
• Long replenishment times in recovering from stockouts.
• High dependence on manual interventions and reactive decisions.

Given this context, it became essential to analyze the value stream, identify end-to-end blockers, and define an achievable future state within a 12-month horizon.

Challenges identified across the supply chain

The organization faced significant supply chain challenges that impacted on-shelf product availability, customer service levels, and end-to-end operational efficiency. These challenges occurred despite the existence of inventory at different points in the chain, indicating structural issues in material and information flows.

The main challenges identified were:

Demand variability and bullwhip effect

The analysis revealed high upstream demand variability compared to actual demand recorded at the point of sale (POS). Orders placed by different stakeholders showed significant fluctuations, indicating the bullwhip effect and a direct impact on planning, inventory levels, and operational stability.

Low forecast accuracy

Significant deviations were identified between forecast demand and actual orders placed, with relevant differences across forecast horizons. The lack of alignment among the various points in the chain and delayed access to critical information, such as promotions, price changes, and inbound and outbound, negatively affected forecast accuracy and service level performance.

On-shelf availability (OSA)

Historical data indicated shelf availability levels below previously established targets. Various in-store observations showed that a significant portion of stockouts were not associated with supply failures at distribution centers, but rather with non-standard replenishment processes and inconsistent practices for detecting and replenishing empty spaces.

Inventory misalignment

Inventory analysis revealed deviations between actual values and target values for DOS (Days of Stock) and DOH (Days on Hand), as well as significant variability throughout the year. During certain periods, excess stock was observed, while in others, there were shortages, highlighting a misalignment between planning, execution, and actual demand.

Operational inefficiencies and lead times

Inefficiencies were identified in logistics processes, particularly in inbound operations, picking, repacking, and repalletizing at distribution centers. These inefficiencies resulted in high lead time variability, increased rework, and consequently a greater operational workload, affecting responsiveness in recovering from stockouts.

From analysis to action: Addressing the identified challenges

Based on the conclusions of the end-to-end Value Stream Mapping (VSM), a set of structured solutions was defined to remove the identified flow blockers across the supply chain, from distribution centers to retail shelves.

The solutions were organized into priority initiatives, defined according to expected impact and implementation effort.

Improving the in-store replenishment process

To standardize the in-store replenishment process, a solution was defined to address the inconsistencies identified during the current state analysis. The implemented solution included:

• Definition of a structured replenishment process, combining replenishment at specific times of the day with frequent detection of empty shelf spaces, as well as continuous replenishment from in-store storage.
• Systematic monitoring of on-shelf availability (OSA).
• Definition of clear criteria for monitoring daily operational performance.

Figure 2 – New in-store replenishment process

Redesign of layouts and planograms

The review and standardization of store layouts and planograms was defined to align space organization with picking and replenishment processes at distribution centers. The solution included:

• Definition of standard layouts by store cluster.
• Optimization of shelf space allocation per SKU based on sales criteria.
• Better use of shelf depth.
• Alignment between store layout and sorting logic at distribution centers.

Centralization of the store ordering model

The ordering process was manual, inconsistent across stores, and highly reliant on individual decisions, which contributed to stockouts and excess inventory.

To reduce variability and dependence on manual decisions, the centralization of the store ordering model was defined through:

• Implementation of an automated calculation of order quantities.
• Integration of demand forecast data, sales history, and stock levels.
• Reduction of the need for manual adjustments to system-suggested quantities.
• Definition of mechanisms to monitor store performance in the ordering process.

This model reduces manual intervention and increases overall order accuracy and consistency.

Joint forecasting across the supply chain

The implementation of a joint forecasting model was defined, involving the different stakeholders in the supply chain. The solution included:

• Alignment of demand forecasts across the various points in the chain.
• Use of direct sales data (POS) as the basis for planning.
• Structured sharing of relevant information, such as promotions, price changes, and products inbound/outbound.
• Definition of review routines and responses to deviations between forecasted and actual demand.

Minimization of repalletizing

Repalletizing was identified as one of the largest sources of waste. Based on inefficiencies identified in logistics processes, a solution was defined to reduce the need for repalletizing, including:

• Alignment of pallet formats across the different points in the chain.
• Review of handling and storage requirements.
• Simplification of inbound and outbound flows at distribution centers.

Improving repacking processes

The process had an average lead time of 20 days, with multiple inbound and outbound movements through the company’s distribution center.

A solution was defined to reduce waiting times and increase efficiency in repacking operations, which included:

• Review of rework operations production capacity.
• Reduction of batch sizes and the number of line changeovers.
• Review of product inbound and outbound flows.
• Analysis of alternatives to reposition rework operations upstream.

Improving distribution center performance

Specific solutions were defined to optimize distribution center performance, covering:

• Improvement of inbound processes, including early shipment visibility.
• Review of sorting and shipping processes.
• Optimization of operational productivity.
• Reduction of lead time variability.

From plans to achieved results

The initiatives led to substantial improvements in both quantitative and qualitative results:

Quantitative results

The quantitative results identified based on the Value Stream Mapping (VSM) and the analyses conducted are as follows:

On-shelf availability (OSA)

Average shelf availability, based on historical data from previous years, stood at:

• 75% for one of the product families analyzed.
• 86% for another product family.
• 83% considering the total portfolio analyzed at the retailer.

Store observations conducted during the first quarter of the impact analysis year indicated average values of:

• 88% for one product family.
• 94% for another product family.

It was found that 67% of the observed shelf stockouts were not attributable to supply failures at distribution centers.

Sales

The analysis indicated that a 2-percentage-point (pp) increase in on-shelf availability corresponds to approximately a 1% monthly sales impact.

Based on the defined availability targets, the following impacts were identified:

• $4.68 million in additional sales for one product family.
• $0.52 million for another product family.
• $16.58 million when extrapolated to the total portfolio analyzed.
• An impact of  $280 million inannual sales when extrapolated to the entire retailer.

Forecast and service level

• Average forecast accuracy showed a MAPE (Mean Absolute Percentage Error) of approximately 52%.
• A target was defined to reduce MAPE to 28%, considering industry benchmarking and a three-month forecast horizon at the SKU level.
• Observed service levels averaged:
  • 74% at one distribution center.
  • 85% at another distribution center.
• It was identified that 62% of service level failures were associated with forecast inaccuracy.
• Target service levels were set as:
  • 90% at one distribution center.
  • 94% at another distribution center.

Inventory

• The analysis showed DOH/DOS values above defined targets, with significant variability throughout the year.
• Opportunities were identified for:
  • Reducing safety stock.
  • Better aligning inventory with actual demand.
  • Improving overall inventory health.

Operating costs

The savings achieved were derived from:

• Reduced overtime hours at distribution centers, estimated at approximately $158,000.
• • Reduced handling costs associated with repalletizing:

• $832,000 ininbound operations.
• $64,000 in outbound operations.

Additional savings were also identified related to reduced rework and improved operational productivity.

Qualitative results

In addition to the quantified results, the following effects were also identified:

• Greater visibility of material and information flows across the supply chain.
• Better alignment among the different stakeholders involved in the value stream.
• Greater standardization of operational processes, particularly in replenishment and ordering processes.
• Reduced dependence on manual interventions in planning and execution processes.
• Greater clarity in identifying flow blockers and action priorities.

The results enabled the objective, systematic identification of the main flow blockers across the supply chain and the quantification of the impact of variability, forecast inaccuracy, and operational inefficiencies on on-shelf availability, inventory, and service level. These results provide a factual basis for prioritizing the defined initiatives and for monitoring performance evolution over time.

Cross-functional benefits achieved

Based on the results identified through the end-to-end Value Stream Mapping, the following cross-functional benefits were consolidated.

Sustained improvement in on-shelf availability, supported by more standardized and consistent in-store replenishment processes.

Greater stability in demand planning, resulting from a more aligned forecasting approach among the different supply chain stakeholders.

Better alignment between inventory, actual demand, and operational execution, reducing imbalances across the different points in the chain.

Reduced operational complexity at distribution centers by simplifying logistics flows and minimizing rework and repalletizing activities.

Greater end-to-end visibility of material and information flows, enabling clearer identification of flow blockers and action priorities.

Greater standardization of operational processes, reducing dependence on manual interventions and reactive decisions.

The consolidation of these benefits creates a more resilient, efficient, and customer-oriented supply chain. Improved coordination, reduced errors, and the adoption of consistent practices strengthen the operation’s ability to respond to market needs and sustain long-term performance gains.

Next steps in value stream evolution

To ensure sustainability, scalability, and consolidation of the identified benefits, the following next steps were established:

• Monitoring progress through a governance model, with regular control and monitoring routines.
• Conducting additional assessments in specific value streams, according to the defined plan, to further develop identified opportunities.
• Periodically updating the VSM, ensuring continuous performance monitoring and identification of new flow blockers.

Consolidating these next steps ensures that the implemented improvements are not only sustained over time but also lay the foundation for more stable, predictable, and scalable operations across the entire value chain.

We are committed to respecting our clients’ confidentiality. While we have altered or omitted their names, the results are genuine.