Skip to main content

Blog Archives

Leading European Pharma Retailer Cracks Supplier Challenges

Case Study

Leading European Pharma Retailer Cracks Supplier Challenges

Business Value Delivered
0 %
increase in new product launches
lead time for supplier onboarding was reduced from 1-2 months to less than an hour
product onboarding time was reduced from 2 months to 1 week
0 %
reduction in time taken to close vendor issues

Client Overview

The client is the largest pharmaceutical retailer in the country and offers OTC, prescription drugs, beauty and healthcare products and related services. It has over 400+ stores, 600+ suppliers and sells a wide range of products.

The client faced data and process challenges across its supplier collaboration processes:

New product launches suffered due to extensive quality requirements, leading to only 50% success rate.

here were frequent delays, errors, and associated risks as supplier on-boarding and verification was a paper-based process with 1-2 months of lead time.

Product onboarding was a long-drawn process with iterative approval flows requiring 2 months of lead time. In spite of that, product information was often found to be incomplete.

There was no standardization of interactions between suppliers and the retailer, leading to delays and gaps due to manual errors and ineffective communication.

Lack of a single source of truth on product catalog and product life cycle was leading to price mismatches and poor quality of feature communication.

With increasing new product launches and a low success rate in launching them, the client was looking for a supplier collaboration platform that would ease data and process collaboration to streamline end-to-end vendor processes.

The Challenge

Expedite new product launches to meet category goals

The Solution

1 Supplier Collaboration Platform

Algonomy’s Vendor Link was the preferred choice of the client as it provided 360-degree supplier collaboration that infused speed, agility, and efficiency in its vendor operations. Its comprehensive web-based automation and collaboration features eliminate error-prone repetitive tasks, bring complete transparency across vendor processes, and boost communication between stakeholders to remove operational silos between vendors and retailers.

2 Powerful Business Outcomes

Vendor Link automated the supplier onboarding process, covering the entire range of activities from expressing interest to joining. API integration with the government vendor database was used to auto-fill accurate information about vendors. The entire workflow was structured in a fashion where each persona can track live status and take actions to expedite the process. The client was able to reduce a lead time of 1-2 months for vendor onboarding to less than an hour.

Manufacturing quality assurance is business critical to ensure that OTC products meet the quality standards. Vendor Link’s manufacturing module helped expedite this process. The supplier/buyer was able to upload documents directly to the portal associating products to manufacturing plants. With complete visibility on the source of products, manufacturing plant certifications, and QA process automation, the client was able to achieve faster product approval.

Product onboarding was also streamlined to improve lead time and meet the client’s stringent quality standards. Around 250+ product attributes were auto-filled in the system with the help of GS1 standard datapool. The smart user interface allowed users to efficiently handle 400+ attributes in a single compact view to review and modify product information. As a result, the lead time for product cataloging was reduced to 1 week from the previous 2-3 months.

Communication between vendors and category managers was strengthened through an in-app notifications system that would track each step of vendor processes (approvals, request resubmission, read-unread distinction, etc.). Advanced dashboards enabled complete transparency with quick review of the progress, pending and upcoming tasks for both supplier and retailer. As a consequence, the client was able to close vendor issues 70% faster.

Product lifecycle management was made more efficient by creation of a single source of truth (Master Data) achieved by integrating product and price information with downstream systems (ERS, POS, price management, web shops). This 360-degree view of the product enabled easier audits and price revisions. Price calculator helped teams perform what-if analysis before finalizing the price and hence reduce margin calculation errors.

Vendor Link helped the client transform supplier collaboration from a set of loosely connected processes to a digitized and scalable supplier ecosystem, with streamlined operations and system-wide transparency all the way up to the manufacturing sites. As a result, the client saw a 100% jump in its new product registration post the implementation.

Results
Client background
Challenge
Solution
Get in touch

Explore More Resources on Commerce Personalization

See all customer stories
How Cycle & Carriage Singapore turned WhatsApp into its main channel for events, test drives, and high-net-worth engagement​
Malaysia Conversational AI

How Cycle & Carriage Singapore turned WhatsApp into its main channel for events, test drives, and high-net-worth engagement​

See full story
0 %
Improved lead completion rate
See all customer stories

Looking for a Personalized Demo?

Let’s talk

John Keells Revs -Up Supplier Collaboration & Efficiency

Case Study

John Keells Revs -Up Supplier Collaboration & Efficiency

The Results
0 %
faster supplier onboarding
0 %
faster supplier onboarding
0 %
of invoice processing automated
0 %
reduction in rebate management

The Client

Keells, a subsidiary of John Keells Holdings, is a leading supermarket chain in Sri Lanka renowned for its commitment to offering fresh, high-quality products and exceptional value to its customers. With over 123 outlets and a robust online delivery service, Keells serves a vast clientele daily, relying on a network of more than 700 suppliers to meet consumer demand.

The Challenge

Despite its success, Keells faced several challenges in supplier management, hindering its growth potential.

  • Manual and error-prone supplier onboarding and product information management, leading to delays.
  • Frustration among large suppliers due to the management of a high volume of purchase order modifications.
  • Inefficient resolution of invoice and delivery disputes, resulting in delayed payments and strained supplier relationships.
  • Rebate calculations was a time consuming affair often requiring extensive data manipulation
  • Lack of data visibility for Keells and its suppliers, hampering timely insights on sales, inventory, and category performance.
The Solution

1 The ROI of Algorithmic Merchandising

As a result of the above, the client achieved significant improvement in its profit margins and was able to optimize its pricing and promotions processes. Revenue leakage was plugged by $5 million with zero instances of accidental double IRs. The client reduced their lead time for instant rebate implementation from 7 days to 4 hours. The client also reduced the planning efforts of category managers, allowing them to focus equally on all categories. The added capability of scenario simulation helped the client bring agility into planning and avoid the disconnect between supply chain and promotions.

2 Algonomy’s Solution Fosters True Supplier Collaboration

Keells adopted Algonomy’s Supplier Collaboration Platform, a comprehensive web-based solution designed to enhance collaboration between suppliers and retailers. This platform automated and streamlined supplier processes, facilitating seamless data and insights sharing.

Under the Keells Advance Network Exchange (KANE) initiative, the platform facilitated various critical functions, including:
Rapid Supplier Onboarding
  • Keells streamlined supplier onboarding via the KANE system, digitizing documentation and employing guided approval workflows.
  • This reduced paperwork, accelerated onboarding, minimized errors, and ensured transparent status tracking.
  • Resulted in a remarkable 92% reduction in supplier onboarding time, facilitating quicker access to a broader pool of suppliers.

Learn More
Digital Catalog Management
  • KANE revolutionized product information management, providing a centralized platform for catalog management.
  • Category teams could effortlessly modify product attributes, pricing, and delist products, reducing redundant efforts.
  • Witnessed an 85% reduction in new product onboarding time, enabling swift adaptation to market demands and introducing new products.
EDI-Integration with Suppliers
  • Embraced electronic data interchange (EDI) to seamlessly integrate purchase orders (POs) and goods received notes (GRNs) with large manufacturers.
  • Reduced manual effort, enhanced operational efficiency, and improved supply chain responsiveness.
  • Mitigated the risk of errors and delays associated with manual data entry.
Automated Invoice Reconciliation
  • KANE introduced a sophisticated 3-way invoice matching feature, automating reconciliation for purchase orders, invoices, and goods receipts.
  • Expedited dispute resolution, minimized erroneous payments, and allowed finance teams to focus on value-added activities.
  • Saved time and enhanced overall productivity by automating 81% of invoices.
Collaborative Rebate Management
  • Automated calculation and management of rebates across the vendor network.
  • Eliminated manual calculations, saved time analyzing individual supplier reports, and reduced administrative burden by 30%.
  • Ensured accuracy and consistency in rebate calculations, fostering stronger supplier relationships.
Demand and Insights Sharing
  • Leveraged KANE’s analytical capabilities to enhance collaboration with suppliers by sharing real-time insights into sales, inventory, and category performance.
  • Empowered suppliers to make informed decisions and optimize operations.
  • Strengthened partnerships, facilitated joint initiatives, and drove mutual business growth.
Results
Client background
Challenge
Solution
Get in touch
“Back in the day, our vendor onboarding was all hands-on and error- prone. But with the new KANE system in play, we’ve amped up our onboarding speed by a whopping 92%, kicked errors to the curb, and witnessed a game-changing boost in efficiency and clarity. It’s like a breath of fresh air for our organization-total game-changer.”
Tharindu Dias
Category Manager
Keells Super, Sri Lanka
“The transition to the KANE system has revolutionized our invoice processing. With a streamlined 3-way matching process, our workflow is now more efficient and error-free. The KANE system’s seamless integration has significantly reduced manual efforts, allowing us to process payments faster and with greater accuracy. It has truly transformed our invoicing experience, making it smoother and more effective for both our team and suppliers.”
Damith De Silva
Assistant Manager, Finance
Keells Sri Lanka
“Since implementing the KANE portal, our supplier collaboration has significantly improved. Data accessibility for our suppliers has increased, providing them with valuable insights they previously didn’t have access to. This has streamlined the process of sharing forecasts and receiving supplier confirmations, resulting in significant time savings and enhancing our relationships with suppliers. KANE has proven to be an invaluable tool in our ongoing efforts to optimize supply chain management efficiency.”
Lakna Gunasekera
Manager, Supply Chain Management
Keells Sri Lanka
“Before, our team spent valuable time manually downloading purchase orders and goods received notes from Keells’ system, then tediously uploading them onto ERP. Now, thanks to seamless EDI integration, the process is automated. As soon as the retailer’s category manager generates a PO & GRN, it’s effortlessly and instantly reflected in our ERP, significantly reducing manual effort and streamlining operations.”
Chamika Herath
Customer Service
Unilever, Sri Lanka
“Getting HOD approval for vendor registration used to be a manual marathon. Now, it’s a breeze-we update the system post-approval, and the category manager is automatically in the loop. This streamlined process has supercharged our workflow, ensuring 100% accuracy in master data management. It’s not just simplified; it’s a significant boost for our operations.”
Shanuka Dilshan
Master Data Manager
Keells Super, Sri Lanka
“Our rebate management process has been transformed with the introduction of the KANE portal. We now receive data directly from category managers, collaborate on updates, and generate reports effortlessly. By automating calculations and streamlining workflows, we’ve increased accuracy and efficiency, allowing us to focus on strategic initiatives.”
Shajila Weerasekara
Assistant Manager, Category Management

Explore More Resources on Commerce Personalization

See all customer stories
How Cycle & Carriage Singapore turned WhatsApp into its main channel for events, test drives, and high-net-worth engagement​
Malaysia Conversational AI

How Cycle & Carriage Singapore turned WhatsApp into its main channel for events, test drives, and high-net-worth engagement​

See full story
0 %
Improved lead completion rate
See all customer stories

Looking for a Personalized Demo?

Let’s talk

Middle Eastern Grocery Retailer Projects $60M Inventory Savings

Case Study

Middle Eastern Grocery Retailer Projects $60M Inventory Savings

Business Value Delivered
0 $
Reduction in inventory cost across 3 departments for the flagship store
0 M
$ Projected savings in inventory costs across 300+ stores
0 %
Reduction in and out stock instances with 90% shelf availability

The Client

Client is a major retailer based out of the Middle East. They are the pioneers in food wholesaling, grocery stores and malls. The company operates 300+ stores across multiple formats such as supermarkets and hypermarkets, convenience stores and wholesale outlets.

The client was looking for an enhanced demand forecasting and replenishment framework that could help them gauge accurate daily and monthly inventory requirements across stores. They set themselves a target of reducing inventory cost by 20% while not jeopardizing availability.

The client, already an existing user of traditional demand planning tools, strongly felt the need of a new replenishment framework that captures dynamic demand forces induced due to shifting consumer behavior and channel complexities while also cognizant of the as-is state and parameters of the supply chain. The client hoped that such a framework would help them cut down inventory cost without compromising on availability.

The Challenge

Achieve inventory reduction by 20% while maintaining availability above 90%

The Solution

1 Hyperlocal Replenishment with Order Right

Algonomy’s demand forecasting and replenishment solution, part of its larger merchandise AI suite of solutions for retail, was the perfect match for the client’s requirement. It uses unique and retail-native handcrafted algorithms to achieve a near-perfect match between demand and supply. Its plug and play ability allows retailers to quickly realize return on investment without having to spend organizational resources in setting up or compromising on key business metrics.

As a part of its larger engagement the client wanted to focus on optimizing inventory cost across 3 departments for its marquee store located in the heart of the city. These 3 departments were – grocery salt, confectionery, and personal care. The combined count of categories under these departments was 200+. The choice of the departments was based on the fact that these departments had witnessed the most increase in inventory cost over the past year.

Algonomy’s demand forecasting and replenishment solution (Order Right) was configured and ready to use within two weeks of data integration.

With the help of Order Right, the client was able to automate and optimize replenishment schedules for 200+ categories across the 3 departments on a single platform without having to use multiple tools, systems and back of the hand calculations. As a result, the client was able to reduce inventory levels by 21% and also witnessed a 9% reduction in out of stock instances.

Order Right’s retail-native demand forecasting technique uses an ensemble of algorithms (2000+ unique algorithms including machine learning and deep learning algorithms) to predict demand for products.

These algorithms account for not just internal factors such as historical sales, promotions and inventory levels but also exogenous factors such as weather, festivals and events that affect demand. The outcome therefore is a more dynamically linked demand forecasting than traditional demand planning tools.

This predicted demand for products in conjunction with supply chain parameters such as lead time, minimum order quantity, fulfillment rate, etc. and category factors such as expiration date and shelf life are then fed into a a unique replenishment optimization engine to generate optimized replenishment schedules.

Results
Client background
Challenge
Solution
Get in touch

Explore More Resources on Commerce Personalization

See all customer stories
How Cycle & Carriage Singapore turned WhatsApp into its main channel for events, test drives, and high-net-worth engagement​
Malaysia Conversational AI

How Cycle & Carriage Singapore turned WhatsApp into its main channel for events, test drives, and high-net-worth engagement​

See full story
0 %
Improved lead completion rate
See all customer stories

Looking to up your replenishment game?

Let’s talk

PanAsian Health & Beauty Retailer Shrinks OOS by 60%

Case Study

PanAsian Health & Beauty Retailer Shrinks OOS by 60%

The Results

Algonomy’s Order Right helped the client transform from static and inefficient to ultra-granular and intelligent replenishment, thereby unlocking business benefits including:

Business Value Delivered
0 %
Reduction in Out-of-Stock Instances
0 %
Improvement in Inventory Turnover
0 %
Reduction in Inventory Investment

The Client

The client is a pan-Asian health, beauty, and wellness retailer. It has over 1100 stores spread across 13 countries providing a wide range of healthcare, beauty care, personal care, and baby care products.

The Challenge

The client is a pan-Asian health, beauty, and wellness retailer. It has over 1100 stores spread across 13 countries providing a wide range of healthcare, beauty care, personal care, and baby care products.

 

  • Product Variety and Seasonality: The existing replenishment process struggled with maintaining stock levels, leading to frequent out-of-stock situations for some products and excessive inventory for others.
  • Promotional Impact: Post-season inventory often piled up following promotional campaigns.
  • Global Supply Chain Complexities: Dependence on multiple suppliers across global supply chains caused significant lead time variances, resulting in out-of-stock issues, particularly during peak seasons.
  • Increasing inventory costs: In its endeavor to achieve high availability, the client witnessed a significant increasing trend in inventory investments.

The client was looking to transform their replenishment framework from static and one-size-fits-all to dynamic and localized. Additionally, they were looking for a solution that could improve planning efficiency, reducing the burden on teams to plan granular replenishment.

The Solution

1 Hyperlocal Replenishment with Order Right

Algonomy’s Order Right perfectly met the client’s need for an ultra-granular, robust, and adaptive replenishment ordering system. Order Right utilizes a suite of custom machine learning algorithms that adjust to demand and supply chain dynamics at a hyperlocal level, accounting for both increases and shifts in demand. Its robust framework swiftly addresses retail data challenges such as sparse data, outliers, and noise, allowing your teams to focus on business without worrying about data interventions.

2 Unlocking Retail Excellence with Hyperlocal Precision and Dynamic Inventory Management

Algonomy’s Order Right helped the client to automate and optimize replenishment schedules for ~500 categories across all store locations in 13+ geographies via a single integrated interface. Here are the key highlights of the solution:

Ultra-Granular Multi-Variate ML-Based Forecasting

With Order Right, the client transitioned from manual, Excel-based forecasting reliant on historical sales to multivariate, ML-based forecasting that accounts for channel, category, and store-specific nuances at the hyperlocal level. This new approach incorporates factors such as product lifecycle, promotions, holidays, and events. As a result, demand planners achieved increased forecasting accuracy across product locations, leading to substantial downstream benefits.

Auto-Optimization for Promotional Effects

Previously, the client relied heavily on manual interventions to adjust for demand fluctuations caused by promotions. This often led to sub-optimal outcomes, resulting in excess stock of some products and out-of-stock situations for others within the same category. With Order Right, the client transitioned to automatic adjustments of product orders to counter promotional effects, significantly reducing inventory imbalances.

Modeling Supply Chain Constraints

The client heavily relied on global suppliers for its products, so any disruptions in the supply chain often came as a surprise, causing teams to scramble to manage the situation and devise tactics to protect the business. With Order, the client transitioned from a static, contract-based supply chain approach to dynamic modeling. Now, the client can optimize replenishment plans using self-learning models that account for key constraints such as lead times, pending orders, expiry dates, minimum order quantities, ordering frequency, and minimum display quantities. This ensures that replenishment plans dynamically adjust to supply chain constraints, resulting in greater accuracy and less crisis management.

Effortlessly Leveraging Retail Data

Order Right’s robust demand forecasting framework helped demand planners circumvent data challenges such as sparse data, noisy data, outliers, and new product introductions effortlessly with custom retail-tuned algorithms. This significantly reduced the efforts required by the team to get quality data.

Results
Client background
Challenge
Solution
Testimonial
Get in touch
“Our earlier vendor management processes were majorly manual, siloed, and prone to errors, leading to productivity losses and increasing supply chain costs. Vendor Link has made it easy and effective for our teams to collaborate with suppliers to manage orders, track payments, and share metrics with them. As a result, our promotions and programs are more efficient, our stock availability has improved, and we have managed to be efficient with our costs while continuing to grow and expand our business.”
Rina Janine Go
Chief Merchandising
Marketing and Distribution Officer Prince Retail

Explore More Resources on Commerce Personalization

See all customer stories
How Cycle & Carriage Singapore turned WhatsApp into its main channel for events, test drives, and high-net-worth engagement​
Malaysia Conversational AI

How Cycle & Carriage Singapore turned WhatsApp into its main channel for events, test drives, and high-net-worth engagement​

See full story
0 %
Improved lead completion rate
See all customer stories

Want to achieve similar results for your grocery retail business?

Let’s talk

Leading Grocery Retailer Slashes Stockouts by 63%

Case Study

Leading Grocery Retailer Slashes Stockouts by 63%

The Results

  • Reduced cost of order to pay cycle management
  • Faster, error-free PO and payment processing
  • Enhanced stock availability
  • Improved promotions effectiveness
  • Improved collaboration planning
Business Value Delivered
0 %
Reduction in Out-of-Stock Instances
0 M
$ Savings on Inventory Cost
0 %
Reduction in Inventory Investment
0 K
$ Annual Reduction in Loss of Sales

The Client

One of the leading retail brands in South East Asia with over 100 stores across the region in diverse categories, was grappling with persistent overstocks and out-of-stock events leading to cost bleeds, wastage, and bloated inventory costs, which spurred secondary challenges like lost sales and customer churn.

The Challenge

The client relied on manual interventions to perform demand and replenishment planning. With changing times especially post-2019, the client felt that their current system was inadequate to respond to shifts in demand patterns and supply chain challenges. The client faced a huge dip in replenishment accuracy and stock issues were rampant across multiple product locations, among other challenges, such as:

 

  • Frequent out-of-stock due to demand volatility and inability to respond to supply chain disruptions
  • Promotions would often lead to stockouts and overstock situations leading to customer distress and margin erosion respectively
  • Leveraging Retail data was proving to be a challenge as it needed support from data scientists to treat for sparse data, outliers, and noise. New product launches were often fraught with huge planning inaccuracies.

 

The client was looking for a comprehensive, intuitive, scalable, and robust AI/ML-based solution to generate precise order plans, and avoid stockouts and overstocks while optimizing inventory and improving shelf availability in an accurate and timely manner.

The Solution

1 Hyperlocal Precision with Order Right

Algonomy’s Order Right perfectly met the client’s need for an ultra-granular, robust, and adaptive replenishment ordering system.

Order Right utilizes a suite of custom machine learning algorithms that adjust to demand and supply chain dynamics at a hyperlocal level, accounting for both increases and shifts in demand.

Its robust framework swiftly addresses retail data challenges such as sparse data, outliers, and noise, allowing your teams to focus on business without worrying about data interventions.

2 Fine-Tuning Replenishment to Hyperlocal Demand and Supply Chain Dynamics

Algonomy’s Order Right helped the client to automate and optimize replenishment schedules for 200+ categories across all store locations in the region via a single platform. Here are the key highlights of the solution:

 

Hyperlocal ML-based Demand Forecasting

With Order Right, the client transitioned from sales heuristics-based demand forecasting to ML-based multi-variate demand forecasting at a highly detailed level. The models were trained using various factors such as product hierarchy, holidays, events, promotions, discounts, and demand deviations. Order Right automatically selects the optimal model for each product-location combination based on best-fit criteria, significantly improving the demand forecast accuracy for 90% of SKUs.

 

Curbing Cannibalization and Promotional Chaos

The previous replenishment framework depended on manual interventions to account for promotional effects like cannibalization. With Order Right, the client shifted to automated adjustments of replenishment levels, both up and down, between products, taking into account promotions and availability.

 

Mitigating Supply Chain Disruptions

Before Order Right, the client depended on suppliers to deliver according to agreed-upon contracts, and any deviations from the SLAs caused stockouts and supply chain disruptions. With Order Right, the client transitioned to dynamic modeling of key factors like lead time, MOQ, minimum size pack, safety stock, display minimums, and pending orders to optimize order plans.

 

Optimizing Multi-Echelon Inventory

The previous approach of using multiple sheets and systems for order management at different supply chain nodes was ineffective and cumbersome. With Order Right, the client moved to centralized multi-echelon inventory management across stores, warehouses, and stocking points.

 

Effortlessly Leveraging Retail Data

Order Right’s robust demand forecasting framework helped demand planners circumvent data challenges such as sparse data, noisy data, outliers, and new product introductions effortlessly with custom retail-tuned algorithms. This significantly reduced the efforts required by the team to get quality data.

3 End-to-end Campaign Management with Marketing Services

  • In addition to leveraging tech, McDonald’s worked with Algonomy’s analytics and campaign specialists to extend its marketing team’s capacity to run campaigns.
  • The specialists helped with the setup, execution, tracking, measurement, and reporting for optimizations.
  • Moreover, the specialists assisted the CRM team and Operations team with ad-hoc analyses around insights for store operations, CRM program objectives, limited-time offers, menu combos, etc.
  • With Marketing Services, McDonald’s set up complex journeys for multiple customer lifecycle scenarios (New Customers, Returning Customers, Lapsed Customers) across channels.

Vendor Link’s collaborative features and data sharing capabilities have helped Prince Retail and its suppliers in several ways. It enabled suppliers and category managers to plan faster and more accurately for promotions, inventory, and other programs.

The platform has helped Prince Retail become more adaptive. For example, it has helped them reduce inventory and other costs associated with products and promotions that don’t do as well as expected.

Vendor Link has also bolstered data-driven decision making on the supplier side. For example, the platform provided shopper insights based on POS data to suppliers.

With this, suppliers get a view of real demand in stores based on consumer sentiment, not just based on purchase orders issued by Prince. This helps them with their own forecasting to improve their relevant assortment and stocks availability, which helps Prince Retail get better stocks allocation, relevant promoted packs and assortment.

Results
Client background
Challenge
Solution
Testimonial
Download Case Study
“Our earlier vendor management processes were majorly manual, siloed, and prone to errors, leading to productivity losses and increasing supply chain costs. Vendor Link has made it easy and effective for our teams to collaborate with suppliers to manage orders, track payments, and share metrics with them. As a result, our promotions and programs are more efficient, our stock availability has improved, and we have managed to be efficient with our costs while continuing to grow and expand our business.”
Rina Janine Go
Chief Merchandising
Marketing and Distribution Officer Prince Retail

Explore More Resources on Commerce Personalization

See all customer stories
How Cycle & Carriage Singapore turned WhatsApp into its main channel for events, test drives, and high-net-worth engagement​
Malaysia Conversational AI

How Cycle & Carriage Singapore turned WhatsApp into its main channel for events, test drives, and high-net-worth engagement​

See full story
0 %
Improved lead completion rate
See all customer stories

Want to achieve similar results for your grocery retail business?

Let’s talk

Prince Retail Transforms Supplier Collaboration with Vendor Link

Case Study

Prince Retail Transforms Supplier Collaboration with Vendor Link

The Results

  • Reduced cost of order to pay cycle management
  • Faster, error-free PO and payment processing
  • Enhanced stock availability
  • Improved promotions effectiveness
  • Improved collaboration planning

The Client

Based in Cebu City, Prince Retail is a chain of retail and wholesale stores that was founded in 1990 by Robert Lim Go. Operating under the Prince Hypermart banner, Prince Retail is a one-stop shop, providing customers with a wide variety of grocery, general merchandise, and department store items.

The retailer has over 67 stores spread across Luzon, Visayas, and Mindanao. Its network of over 500+ suppliers helps it serve its mission of ‘serving the underserved’, focusing on Filipino shoppers in far flung and rural and island provinces and providing quality products at affordable prices with a convenient and comfortable shopping experience.

The Challenge

As one of the fastest-growing retailers in the Philippines, Prince Retail faced multiple challenges that could impede its growth plans.

One of the major challenges it faced was the increasing complexity and cost of vendor management due to a lack of collaboration and transparency between its merchandising team and suppliers.

Vendor processes—order management, scheduling, payments, promotions, demand planning, and reporting—were operating in silos and prone to manual errors.

The retailer’s vendors showed low confidence in the data that was currently being shared – often leading to longer lead times, low fulfillment rate and stock availability at the stores. As a result, vendors were less proactive in their approach to promotions and other programs.

The Solution

1 Intelligent & Agile Supplier Collaboration with Vendor Link

With the above challenges at the fore, Prince Retail was looking for a solution that could:

  1. Streamline and optimize fragmented and siloed vendor processes such as order to pay cycle, stock allocation, promotions planning, and reporting.
  2. Create a hyper-connected vendor ecosystem that shares shopper insights and reports with vendors to help them with planning and promotions.
  3. Accelerate digital transformation and build data-driven decisioning both internally and externally to achieve operational excellence.

Algonomy’s Vendor Link fit in perfectly with the client’s requirement of a 360-degree supplier collaboration platform. Vendor Link is a comprehensive web-based vendor and retailer collaboration platform that removes operational silos between vendors and retailers by automating and streamlining end-to-end operations, and sharing data and insights across category, sales, and inventory.

Vendor Link helped Prince Retail’s buyers better manage purchase orders across stores. Siloed communication and follow up emails and calls were replaced with a centralized web-based order tracking system accessible by vendors.

As a result, manual errors were eliminated, and buyers and vendors were able to spend more time on value-adding activities.

Vendor Link also improved payment visibility wherein vendors can now track their payment status in real time and improve their delivery schedule to Prince Retail, hence boosting shelf availability.

2 The ROI of Automated Supplier Management

The client benefited from Vendor Link in the following ways:

  • With the help of Vendor Link’s tracking and collaborative features, PO and payment processing became significantly faster, transparent, and error-free. As a result, the customer was able to reduce costs and improve effectiveness in order to pay cycle management.
  • Vendor Link enabled interactive on-demand access to data insights and reports for suppliers. Buyers and Finance teams can now easily share data, insights, and reports with vendors and vice-versa. This improved system transparency, helping teams run effective programs with reduced costs.
  • The client witnessed reduction in vendor disputes and an overall improvement in vendor buyer collaborative planning. As a result, client stores witnessed improved stock availability and promotion effectiveness.

Vendor Link helped Prince Retail streamline its order management process, bring transparency in its payment processing, and build a data-driven culture across its vendor ecosystem. As a result, Prince Retail saw improvement in product availability and promotions, reduction in costs, and improvement in vendor satisfaction.

3 End-to-end Campaign Management with Marketing Services

  • In addition to leveraging tech, McDonald’s worked with Algonomy’s analytics and campaign specialists to extend its marketing team’s capacity to run campaigns.
  • The specialists helped with the setup, execution, tracking, measurement, and reporting for optimizations.
  • Moreover, the specialists assisted the CRM team and Operations team with ad-hoc analyses around insights for store operations, CRM program objectives, limited-time offers, menu combos, etc.
  • With Marketing Services, McDonald’s set up complex journeys for multiple customer lifecycle scenarios (New Customers, Returning Customers, Lapsed Customers) across channels.

Vendor Link’s collaborative features and data sharing capabilities have helped Prince Retail and its suppliers in several ways. It enabled suppliers and category managers to plan faster and more accurately for promotions, inventory, and other programs.

The platform has helped Prince Retail become more adaptive. For example, it has helped them reduce inventory and other costs associated with products and promotions that don’t do as well as expected.

Vendor Link has also bolstered data-driven decision making on the supplier side. For example, the platform provided shopper insights based on POS data to suppliers.

With this, suppliers get a view of real demand in stores based on consumer sentiment, not just based on purchase orders issued by Prince. This helps them with their own forecasting to improve their relevant assortment and stocks availability, which helps Prince Retail get better stocks allocation, relevant promoted packs and assortment.

Results
Client background
Challenge
Solution
Testimonial
Get in touch
“Our earlier vendor management processes were majorly manual, siloed, and prone to errors, leading to productivity losses and increasing supply chain costs. Vendor Link has made it easy and effective for our teams to collaborate with suppliers to manage orders, track payments, and share metrics with them. As a result, our promotions and programs are more efficient, our stock availability has improved, and we have managed to be efficient with our costs while continuing to grow and expand our business.”
Rina Janine Go
Chief Merchandising
Marketing and Distribution Officer Prince Retail

Explore More Resources on Commerce Personalization

See all customer stories
How Cycle & Carriage Singapore turned WhatsApp into its main channel for events, test drives, and high-net-worth engagement​
Malaysia Conversational AI

How Cycle & Carriage Singapore turned WhatsApp into its main channel for events, test drives, and high-net-worth engagement​

See full story
0 %
Improved lead completion rate
See all customer stories

See How ADA Verify Can Simplify Your Customer Onboarding

Book a Demo

Aditya Birla Fashion and Retail Drives a 13% Lift in AOV Across 6 Brands by Personalizing Key Commerce Touchpoints

Case Study

Aditya Birla Fashion and Retail Drives a 13% Lift in AOV Across 6 Brands by Personalizing Key Commerce Touchpoints

The Results

0 %
lift in recommendations driven AOV on Pantaloons and The Collective
0 %
of attributable sales on Pantaloons
0 %
attributable sales on The Collective
0 %
lift in Revenue Per 1,000 views for AI-driven recommendations vs merchandised recommendations on Pantaloon

Client Overview

  • ABFRL’s vision is to satisfy Indian consumer needs in lifestyle and fashion with product offerings from premium brands.
  • The retailer has embarked on a digital transformation journey with a high focus on delivering personalized omnichannel customer experiences.
  • After a rigorous selection process, ABFRL chose Algonomy as their technology partner as the latter checked all the boxes for product depth and breadth, innovation, and customer success references.

Personalizing All Path-to-Purchase Commerce Touchpoints

  • ABFRL has deployed Algonomy’s AI-powered personalization suite, which comprises:
  • These solutions are live across the ABFRL brands – Pantaloons, The Collective, and Super App.
  • Algonomy’s solutions combine real-time browsing behavior with enterprise-wide customer data to create real-time, unified customer profiles that guide contextual, individualized experiences across all customer channels—including website, app, email, and in-store.
  • The solutions offer the retail industry’s only no-code Data Science Workbench and Configurable Strategies, which help ABFRL’s marketing and merchandising teams build, test, and iterate personalization strategies on the fly.
Results
Client background
Challenge
Solution
Get in touch
“Algonomy’s AI-infused personalization tech has helped us individualize all path-to-purchase digital commerce touchpoints—search, recommendations, browse, and content—to deliver a more holistic and connected customer experience.”
Varun Rajwade
AVP
Product, Design & Digital CX at ABFRL

Personalization Use Cases on the Pantaloons Online Store

Pantaloons is one of India’s largest fashion store brands. The brand has launched ‘Style Finder’ that allows shoppers to specify their preferred categories and the occasion, and view personalized product recommendations.

This feature has significantly improved product discovery in a time when consumers expect brands to make every experience feel personal.

Other examples of personalized experiences on Pantaloons:

The ‘Pick up where you left off’ placement on the home page helps a returning shopper resume their journey instead of having to start over.

Recommendation placement for similar products on Product Detail Pages.

Placement for ‘Deals of the Day’ with offers on products a shopper will likely be interested in.

Complementary product recommendations on the PDP.

Personalized product sorting in search results.

Search results for “trousers” without personalization

Search results for “trousers” with personalization

The ‘Shop the Look’ feature allows a shopper to view complementary products and complete the look.

Helping Shoppers Experience 4 Popular Brands in 1 Intuitive ‘Super App’

Super App allows shoppers to seamlessly switch between four popular and sought-after brands — Louis Philippe, Van Heusen, Allen Solly, and Peter England—on the same website or app.

Shoppers can view personalized products and add items across the four brands to a common cart and complete their purchase.

Some examples of personalization on Super App:

While setting up their account, shoppers can set their preferences for color, categories, size, etc. The personalization engine uses this information, along with the shopper’s browsing patterns and purchase history, to make the most relevant recommendations.

Typically, on most commerce websites/ apps, shoppers have to visit a PDP to find recommendations for similar products. On Super App, however, while viewing various products on a category page, shoppers can just click on the ‘View Similar’ option near a product card, which opens a pop-up containing recommendations for similar products.

Category recommendations on the home page are displayed as per the individual shopper’s tastes. The order of categories changes dynamically with respect to changes in the shopper’s behavioral and purchase patterns.

Personalized content on the home page.

Unifying the Online & Offline Shopping Experience with The Collective & Super App

  • Most retailers tend to think of a customer channel in isolation. ABFRL, however, has seamlessly unified online and offline, delighting customers with unique and memorable experiences.
  • For instance, The Collective (India’s first, and now the largest, multi-brand luxury retail store) and Super App have a feature called ‘Store Mode’ on their websites. The feature allows online shoppers to view personalized products from a certain physical store, and have products delivered to their homes.
“Shoppers today expect their digital shopping experience to be quick, seamless, and personalized as per their individual tastes and intent. Algonomy’s end-to-end personalization solution was the perfect fit, given our massive scale and speed requirements.”
Praveen Shrikhande
Chief Digital & Information Officer
ABRFL

Explore More Resources on Personalized Marketing

See all customer stories
How Cycle & Carriage Singapore turned WhatsApp into its main channel for events, test drives, and high-net-worth engagement​
Malaysia Conversational AI

How Cycle & Carriage Singapore turned WhatsApp into its main channel for events, test drives, and high-net-worth engagement​

See full story
0 %
Improved lead completion rate
See all customer stories

Ready to see ADA Find™ in action? Let’s talk.

Book a Demo