A RECIPE FOR SUCCESS: DIGITAL TRANSFORMATION OF THE RESTAURANT SUPPLY CHAIN
How a global restaurant company achieved best-in-class forecast accuracy, reduced inventory by almost 50%, and eliminated bullwhip effect across their supply network
“This solution has allowed us to achieve best in class forecast accuracy levels, from the low 60s to the high 80s. We have essentially eliminated the bullwhip effect, and we have improved the efficiency of our inbound supply chain, reducing many, many of our suppliers’ costs… Along with this fresh product, we have been able to reduce inventory by nearly 50% and certainly, we have been optimizing costs all along the way.”
– Bloomin’ Brands
The restaurant supply chain has been heavily stressed, both before and after COVID-19.
Even before the outbreak of COVID-19, the Fine and Casual Dining industry was under tremendous pressures due to increasing competition, rapidly shifting customer preferences, as well as customer expectations of world class service featuring only the freshest ingredients. These, and other restaurant supply chain challenges, combined with the recent COVID-19 pandemic, has pushed many restaurants and chains to the brink.
Increasing Complexity and Vulnerability of the Restaurant Supply Chain
Meanwhile, escalating food safety and sustainability concerns require full traceability of lot distribution and of ingredients to the source of supply. Simultaneously, businesses have grown in complexity to depend on local distributors supplemented by international distributors and logistics providers.
This has led to restaurant chains losing control of their supply chains, along with an ever-increasing number of stakeholders that must be coordinated to deliver meals to the consumer on time.
Gaining Visibility and Control Over the End-to-End Food and Restaurant Supply Chain
How does One Network’s Real Time Value Network address the challenges in the food and restaurant supply chains?
One Network provides a global planning, optimization and execution backbone that the entire distributor and supplier community can leverage to be highly responsive to consumer dining habits. This cloud network allows enterprises to realize rapid results, and to leapfrog the results achieved by traditional ERP implementations.
Take Uber as a proven disruptor in the taxi industry. Uber is a network platform that takes demand from consumers world-wide for their personal transportation needs and matches it in real time to a local capacity of drivers. The service is offered at a fraction of the cost of a traditional taxi cab service and at a much higher service level. The car is provided on demand with a very short lead-time (minutes) to pick up the customer. This higher service level at a much lower cost model revolutionized the taxi industry.
Applying the same principles to the restaurant logistics solution, the underlying technology approach is to provide a real-time match of consumer demand to supply, with an execution system to provide the supply of the product or service to the consumer at a much higher service level and at a much lower cost. The network platform already exists that can onboard all trading and fulfillment partners and can coordinate all of their planning and execution activities around consumer demand in real time.
The Fine and Casual Dining Industry is headed for revolutionary change, particularly the restaurant supply chain. The question is who is going to lead this industry?
You need to ask yourself the question, “Do I want to be the next Uber, or the last standing cab company?”
Case Study: How a Leading Global Fine and Casual Dining Restaurant Company Achieved Results
One leading fine and casual dining company opted to move beyond legacy ERP technology augmented by spread sheets to a multiparty cloud network service. Among other capabilities, this single network is replacing as many as nine different ordering systems.
Similar to the Uber model, all parties are represented on this consumer driven demand-supply match solution. This includes corporate and franchise restaurants, store delivery providers, distributors, raw material suppliers, logistics partners, and commodities brokers. All parties work on a common consumer demand forecast aligning all available supply to demand in real time while optimizing operational costs.
Consumer-Driven Restaurant Supply Chain
This restaurant company has revolutionized the supply chain approach by providing a consumer driven pull signal to all parties in the value chain in real time. This is made possible by monitoring consumer demand throughout the day, forecasting projected demand profiles for menu items, and translating those into required raw materials over the multi-tier delivery network from consumer to raw material manufacturers.
They have now achieved over 40% improvement in predicting item-level consumer demand and converting that to required ingredients and operational support.
The Opportunity for Restaurants to Transform Their Supply Chains
Fine and Casual Dining companies can achieve similar results in their forecast accuracy. By on-boarding to a network platform, restaurants, distributors, suppliers, logistics providers and carriers can shape and sense consumer demand and respond together in real time. The significant opportunities for companies in this sector include:
- Demand Shaping such as Limited Time Offers (LTO) and New Menu Items with over 90% forecast accuracy.
- A real-time network eliminates information lead times reducing overall supply lead times which results in inventory reductions across the network, increased turns, and improved freshness (adding 4 days to ingredients available shelf life).
- 50% reduction in inventory from the industry norm of 8-12 days of inventory to only 4-6 days of inventory.
- 10% savings on cost of goods sold by treating distributors as flow through, reducing their inventory, improving their forecast, reducing raw material inventory at stores, and improving logistics operations.
- Restaurant’s order management efforts are reduced by 90%.
- The responsive supply chain network can support omnichannel including: franchises, home deliveries, and online sales. This opens up opportunities for differentiated business models and new revenues that increase customer engagement through mobile and omnichannel offerings.
- Transportation costs are reduced with shared distribution models driven by accurate orders and order forecasts, and by intelligently building efficient shipment loads driven by consumer demand.
- With network technology, any new member (store, supplier, carrier) can instantly start interacting with the entire network. This radically reduces new store time to profitability, new supplier on-boarding, limited time offer mobilization, and new brand introduction times. Process automation via the network enables consistent and optimized operations, driving time to profitability down to 3 months or less.
Optimizing the Restaurant Supply Chain with Intelligent Agents to Enable the Autonomous Supply Chain
In a traditional approach, enterprise silos prevent any one party from having a full picture of demand, supply and execution status to serve the customer. There are too many systems, with redundant, conflicting and incomplete information that must be reconciled and integrated before doing anything useful. It is too slow to go from gathering the data inputs required for planning to executing decisions. Information systems cannot support the speed of business anymore. Furthermore, rigid, “one size fits none” Commercial Off-The-Shelf (COTS) systems require customizations that kill agility and inflate the total cost of ownership (TCO).
Real Time Digital Networks Must Replace Linear Restaurant Supply Chains
Companies must move away from traditional approaches and embrace a new paradigm to keep up with today’s fast-paced business. This new paradigm is consumer-driven, leverages a flexible and modular multiparty network platform and enables dramatic performance improvements that generate unprecedented results.
The key to this approach is the multiparty multi-tier, real-time network service connecting restaurants, distributors, suppliers, logistics providers and carriers via the cloud. Each party only needs to onboard once, and then can interact with all others instantly.
Automating the Restaurant Supply Chain with Artificial Intelligence
NEO, One Network’s intelligent sense-and-learn agent technology, gleans patterns from point-of-sale (POS) data and continuously adjusts forecasts for menu items at the store level. Menu-item forecasts are translated to raw-material-item forecasts. These in-turn drive order forecasts which are further analyzed by NEO, taking into account order units-of-measure, operational lead times and shipping and receiving calendars of every party involved along the way.
Autonomous Order Management
The order forecast for each distribution center is used by supplier systems to plan their inventory and the actual orders are automatically optimized at all tiers for service levels, inventory levels and operational costs. The network automatically generates all orders, tracks them, converts them to shipments and re-computes all inventory levels, calculates all capacities needed (such as labor or dock door availability at distribution centers) and schedules those capacities. An important strength of the solution is that suppliers are not just spokes to the restaurant’s system. They are also hubs in their own respect, enabling them to exploit the power of NEO and the One Network Platform to manage their business for other customers and provide operations and optimization across all their customers, suppliers and logistics providers on the same platform.
Since the entire system is consumer-driven, restaurant orders are automatically created and support all omnichannel needs. Restaurant managers need only be involved when they have local knowledge of a planned increase or reduction in traffic.
All orders are created and managed automatically by the system. Forecasts can be enhanced by planners, but the system has proven that it can plan and re-plan itself with much higher accuracy and agility than a traditional decision-support approach. The system creates optimized shipments and auto tenders based on pre-configured business rules and monitors execution with milestones and tracking events in real time.
This highly automated system moves away from significant user involvement to an exception management process that alerts relevant parties and then assists those in taking corrective actions. This reduces required head count and allows the users who are involved to spend their time resolving only issues NEO cannot solve on his own based on the levers available and constraints.
With the application of the machine learning technology, intelligent agents continuously learn based on changes in business variability or seasonality. More importantly, NEO continuously projects not only what the future holds but translates that into specific financial projections for revenue and margins.
Old ERP systems are unable to support collaborative decision-making in multiparty networks such as in the restaurant business. However, these legacy systems can be seamlessly embraced for accounting purposes, enabling you to take advantage of your historical investments.
A Rapid, Self-funding, Minimal Risk, Agile Implementation
Historically system implementations required a big bang approach to deploy enterprise-only capabilities. This approach proved to be enormously expensive, takes too long and is extremely risky. In addition, it is labor-intensive and costly to support. More importantly, the inability to adapt these systems as business needs change, can hurt the agility of the restaurant businesses.
Multiparty networks are typically deployed within months rather than years, and are deployed with all of your trading partners. This not only drives significant value but also greatly reduces the complexity of the system due to the fact that most activities in the restaurant supply chain are actually managed by your trading partners.
The system is modular, unlike monolithic ERP systems. It allows step-by-step short projects (similar to sprints in an Agile Development Methodology) that are rapid, self-funding, and low risk. The support approach is a never legacy approach allowing for automated upgrades, providing new capabilities on a frequent basis.
“Real time visibility, coupled with demand- based forecasting, will help create a more efficient and agile supply chain.”
– Bloomin’ Brands Inc.
How You Can Get Started
This paper demonstrates how a new paradigm using innovative technologies overcomes fundamental flaws in current approaches and offers the opportunity to unlock enormous value in the Fine and Casual Dining industry. Visionary restaurant companies are already transforming to consumer-driven digital networks and achieving breakthrough results. The choice is clear. Disrupt or be disrupted.