Hubspot Blog Feed
Manufacturers utilizing JIT production are continuously trying to mitigate the volatility of product availability and price within their current supply base. Unfortunately, most JIT facility layouts are designed for limited spatial flexibility to secure those line-side critical parts. The manufacturer, then, is oftentimes left with optimizing capability at the supplier side to maintain on time delivery and production. As an alternative to working through the existing relationship, the manufacturer also looks for additional sourcing opportunities to compete with the highly demanding production schedule and product prices.
Supplier Relationship Management (SRM) Case
CGN understands the value of complete supply chain visibility. By understanding the constraints of the supply base, the manufacturer can better manipulate its operations, buying strategies, and resources to optimize its production needs. CGN recently partnered with a JIT manufacturer in the access equipment industry to manage its current SRM strategies with Supplier A and Supplier B. Supplier A’s on time delivery performance had been under-performing for several months, due to operational and technical incompetencies. Supplier B’s past due slippages were fundamentally a result of production inefficiencies as well but were layered with an added complexity of relational indifference.
CGN identified several opportunities and solutions that were consistently evident across the JIT manufacturer’s under-performing supply base.
CGN’s unique sustainable footprint has been proven successful by designing these solutions with the manufacturer and supplier’s preexisting SRM framework as the basis. When asking Supplier A for root causes on missed delivery, CGN integrated the enhancement into the current communication structure to alleviate any growth pains and focus on delivering immediate productivity results. The newly added reporting metrics alone drove past dues at Supplier A down by 77% in 12 weeks (see below). Conversely, the modified buying strategy by the manufacturer has allowed Supplier B to increase capacity hours by 10% and pallet utilization by 7%. In both cases, CGN focused on driving the relational component of SRM to set up the manufacturer and suppliers with long-term profitable development and visibility to operational and technical improvements.
In a world where organizations are trying to improve their day to day practices and discover new means to improve the efficiency of their business, artificial intelligence (AI), which was once only a concept in Sci-Fi movies, has now paved the way for a more smooth, reliable, and data driven world.Machine Learning (ML), which is a part of AI, makes it possible to discover patterns in data, by relying on algorithms that quickly pin-point the most influential factors affecting change; but it doesn’t stop there.
Below are a five examples of where AI is making waves in manufacturing and supply chain:
1) Machine learning algorithms and apps running AI can analyze large and diverse data sets faster and can improve demand forecasting. With the ability to process large amounts of data, and learn along the way, prediction becomes more accurate. In recent years, manufacturers have leaned towards AI to predict build-to-order processes and make-to-stock production workflows more effective. Manufacturers are reducing supply chain latency for components and parts used in their most heavily customized products by using machine learning. CGN has implemented machine learning algorithms to analyze large amounts of data, find patterns and get clear insights. Another great example would be, an incomplete raw dataset was given and the ask was to find any patterns in the data. CGN used Data mining techniques, Clustering and forecasting algorithms to predict the missing data hence giving greater insights into the data.
2) Reducing freight cost, improving supplier delivery performance, and reducing supplier risk are a few benefits machine learning can provide in collaborative supply chain networks. Companies look at supplier assessments, audits, and credit scores when deciding which supplier best suits their needs. With the help of AI, the data gathered can help supplier selection be more predictive and comprehensible. Components of a certain product can be easily tracked and traced that are inbound from suppliers.
3) Predictive analytics: The Internet of Things (IoT), with production machine sensors, has been gaining a lot of traction around the world. The data collected can help improve overall equipment efficiency (OEE), improve preventative maintenance that in turn can improve OEE and production quality.
- Improve OEE: Most companies use AI only to predict machine failures but miss out on the true potential of AI to improve OEE. When working on change-over time reductions, single minute exchange of die (SMED) techniques measure time from the last part of the previous run to the first good part of the next run. However, there is still time wasted, during this procedure. AI can identify gaps, analyze the data from sensors, and help find patterns that lead to loss of time. Using time stamp data of each job can help in improving OEE and reduce downtime and changeover time.
- Improving Preventative Maintenance Program: Sensor generated data can be analyzed using unsupervised learning algorithms to find deviations that can give an early warning of a component nearing failure.
- Improving the Quality of a Product: When machines are trained (supervised machine learning) with a library of visual data and then combined with sensors to analyze a product, the results can help identify even the smallest of deviations.
4) Chatbots for Procurement: Conversational interfaces (Chatbots) can potentially be used to help businesses by reducing transaction cost and sales cycle time. Suppliers can speak to your bot and get information or plan orders. Additionally, bots can be used to send orders, do paperwork, deal with invoices and payments, without human intervention. Even though companies are slowly adopting chatbots, the technology has a few miles to go before becoming completely autonomous and being used in procurement.
5) Machine Learning for Warehouse Management, Logistics and Shipping: Today AGVs are more autonomous, and with the integration of data from warehouse management software and control systems, AGV’s can do almost everything that a human can do manually.
AI is making its way into logistics control tower operations (LCTO) to provide new insights into how every aspect of SCM, collaboration, logistics and warehouse management can be improved.
At CGN Global, we strive to improve global supply chains for our customers. Using predictive analytics and machine learning, CGN can help businesses win in their supply chain efforts, making supplier relationship management, risk analysis, transportation management and demand forecasting much easier.
Why is it important?
Many companies realize that effective cost management, through the product life cycle, is very important. However, we often see that most of these efforts happen when the product is in the production phase, and there is a need to control costs to improve margins. Many companies try to manage costs during the product development phase with varying degrees of success.
The primary issues with effective cost management, in new product introduction, (NPI) are
- Lack of time – Engineering resources are focused on developing the designs for production and costs are not the highest priority
- Lack of motivation – Cost avoidance is usually not one of the metrics on organizational scorecards, but cost reduction is usually incorporated
- Lack of supplier collaboration on the product design – Suppliers are often treated as manufacturers only, not design partners
However, the benefits of early cost reduction are significant. As shown in the picture below, the biggest cost impact is possible, during the NPI phase, when product specifications, design, and manufacturing processes are being defined. Working on cost reduction projects in the production phase is mostly limited to commercial levers, because design related changes are fairly slow and painful.
What are necessary elements of a successful NPI cost management process?
- Clear cost targets with assigned accountability
- Clear visibility of the product cost at any point in time
- Understanding of the impact of various design choices on cost
- Up-front identification of the supply base and the level of collaboration to drive out maximum efficiency from supplier input
- Focus on costs in all design reviews along with product performance, quality, etc.
There are several tools necessary to facilitate effective cost management structure, like total cost of ownership (TCO), should cost modeling, visibility dashboards, etc. that teams need to be trained on to apply, going forward, for best results.
CGN has worked with multiple clients in the manufacturing space on managing their product cost, throughout the life cycle, and has a suite of tools and techniques that have been proven successful through the years. We help our clients not only identify and validate opportunities, but work side – by – side with them to drive realized product cost savings.
Commercial Analytics is more important than ever before. Today, nearly everything, from events, relationships, movements, transactions, and decisions are all evidenced by data. As the pace of technological advancement increases, it is essential for businesses to develop a data strategy for navigating the sea of data being generated, and, also for the preparation of future implementation of new technologies, like IoT and Artificial Intelligence. A firm’s current and future competitiveness, profitability, and market share depend upon its real-time responsiveness to business and economic conditions. To successfully leverage data through analytics, a firm must collect the correct data, be able to locate it, and ensure the right people have it when they need it.
The business costs associated with the lack of a comprehensive data strategy can often be elusive. Incomplete data, employee time cleaning or finding data, lost sales, delays in access to data, lack of responsiveness to customer needs, poor decisions, and the inability to implement new technologies are all examples of costs that a firm can incur. These costs are often hidden and lurking within a business, making it difficult to see the value in developing and investing in a digital strategy.
The absence of a clear data strategy has several pitfalls. Enterprise data can be stored in employee’s experience rather than a database. When employees leave, they take their knowledge with them and new hires are forced to perform duplicative work. Decision making can also be made retrospectively, either monthly or quarterly, instead of in real-time. Customer needs and behaviors are just as dynamic as the business environment, making timely responses to changes in behavior imperative. Any lag in data or analysis can be extremely costly for controlling variable costs and maximizing revenue. Further, incomplete and inaccurate data can be the foundation for decisions, leading to consistent errors or misguided assumptions. Continually relying on static systems without an overall strategy will only compound mistakes and lead to further declines.
The only way for companies to maintain a competitive edge in today’s dynamic business environment is to treat the production, consumption, and transportation of data like a supply chain. Only then can increased productivity, efficiency, and responsiveness be achieved. The same strategy, planning, and development required for a lean supply chain is required for a firm’s digital strategy. It is important to identify key metrics for a firm’s success and to create visibility of the transactions, behaviors, and data affecting those metrics. Simply having the data is not enough, you must be able to connect the data in a meaningful way to create insights. Then, it is critical to transform any insights into actions and behaviors that create value.
This type of business transformation is not easy. It takes a clear strategy driven by leadership to overcome any organizational silos or resistance to change. Leadership must develop and define a vision of their firm’s digital future and it must guide the planning, implementation, and automation of data processes. It is imperative to develop this vision for a company’s digital transformation because it will likely be the difference in competitiveness and profitability as the pace of change increases and the next disruptive technology is created.
"A bad schedule from a good plan is better than a great schedule from a bad plan," Sanjiv Sindhu, Co-Founder i2 Technologies
Simply put, the main objective of supply chain planning is to accurately estimate the customer needs and ensure that they receive the right products, through the right channels, in the right quantities, and at the right time. However, global competition, political and economic uncertainty, and evolving technology and trends towards customization have made managing company supply chain planning a tough task.
In good economic times, when businesses are flourishing, companies experience significant increases in demand. Company manufacturing plants are overburdened. Supply bases become constrained and time to market increases. During such periods, manufacturers look for innovative solutions to improve processes, so no opportunity is lost. The focus needs to be on a well-defined supply chain and demand prioritization planning, as it impacts the end-to-end process, starting from inventory management to logistics and customer service. It is vital to understand how production resources are planned and scheduled.
Creating an optimal production plan by gaining visibility to man, machine and material constraints ahead of time; has a significant impact on the supply chain performance. Optimal production plans help alleviate the following:
- Overhead costs, during unplanned excess demand (bottleneck situations, overtime, etc.)
- Excess inventory buildup, during unexpected downturns
Demand prioritization plays a key role in determining the optimal production sequence that drives maximum profitability. Demand is prioritized by several factors, including organizational profit, customer service, and demand volume. This prioritized demand is communicated through a "control tower" mechanism to drive a production sequence that strikes a balance between profitability and customer service.
The image below illustrates the key nodes and points of contact involved in the information and material flow as part of demand prioritization process.
CGN Global is currently guiding a Fortune 50 manufacturing company, experiencing a significant growth in demand to meet its build commitments, by assuring material supply and minimizing line down situations. Capacity constraints at critical suppliers and accumulating past dues, caused the manufacturer to frequently re-plan build schedules. As a result, demand signals from the client’s several manufacturing facilities are inconsistent and uncoordinated, causing inefficient utilization of supplier capacity.
As a solution, CGN has deployed its “Supplier Constraint Management” methodology, which proactively responds to real-time issues through a “control tower” mechanism. This advanced planning solution can help satisfy the client's demand, considering prioritization rules, supplier responsiveness, and production capacities. The planning process in place creates the ability to drive the supplier commitment to schedules and escalate any shortfalls within the frozen window. The data insights provided by the solution accelerates decision making to real-time action and raises the supply chain agility to a different level.
At CGN, we help companies worldwide overcome core business challenges of growth, margin, and responsiveness. Going beyond simply solving their problems, we quickly and effectively deliver transformational results that are sustainable.
Business Value of Aftermarket Services in OEMs
"A business absolutely devoted to service will have only one worry about profits. They will be embarrassingly large,” -Henry Ford, founder of one of the world’s largest manufacturing companies. This is the golden age of services. To survive and prosper, every company must transform itself into a services-based business.
For original equipment manufacturers (OEMs), in mature markets, such as Europe and the US, aftermarket business has already become the most important source of revenue and profits. According to global statistics, service and parts business (SPB), on average, account for more than 35% of total OEM revenues; for a third of OEM’s, the revenue generated from their SPB often contribute more than 50% of the total. In addition, profit margins for the SPB are usually higher than that of traditional vehicle sales. Within mature markets, profit margins for SPB are 76% higher than that of the conventional finished product business; for 70% of the OEMs, the profit margin for SPB is more than 25%, and for 34% of the OEMs, the margin for parts business is even higher than 40%. As an OEM, energizing efforts to increase market share in the aftermarket is crucial for growth, but also comes with its own challenges as well.
Challenges in Aftermarket Services
Recent information by Fortune 500 heavy equipment and automotive manufacturers indicates some common challenges: a) tapping into wealth of real time customer data; b) sharing information at various levels; c) inconsistent service; d) service parts inventory carrying costs; e) increasing revenue streams from installed base.
Studies show that US OEMs and their dealers may be losing $9-15 billion in aftermarket sales annually, to competitors. OEMs and dealers could bill billions of dollars more if they knew how to constantly collect information from the installed machines for sales and service opportunities. 70% of business buyers would make purchases online, rather than through another channel, but OEMs have less than 20% visibility into their parts e-tail market and their “genuine parts” program revenue growth may be in jeopardy. OEMs suffer from limited remote equipment connectivity, leading to incomplete and often inaccurate installed base management. Unscheduled downtime, high service delivery variance, and sub-optimal data analysis lead to lower efficiencies and reduced effectiveness and cause cannibalizations and brand value dilution.
OEMs and their dealers can emerge from this conundrum, if they better capture and manage both machine-chatter and consumer chatter in a unified platform through digitization of end-to-end value chain.
Digitization – A new era for Aftermarket services
Supply chains are traditionally linear in nature; a series of largely discrete, siloed steps taken through marketing, product development, manufacturing, distribution, and finally into the hands of the customer (Figure1). Digitization will change this approach, bringing down walls and creating a completely integrated ecosystem that is fully transparent to all the players involved. This ecosystem will depend on several key digital technologies, including logistics platforms, analytics, robots, and 3D printing. Digital supply chains (DSCs) can hold extensive information and provide superior collaboration capabilities that result in improved reliability, agility and effectiveness (Figure 2).
Figure 1. Traditional Supply Chain Model
Figure 2. Digital Enabled Supply Chain (DSC) Model
A Digital Operating Model supports a more flexible organizational design, as information is no longer location dependent. To realize the full potential of being a global organization, companies must take a closer look into internal alignment committees and procedures, service level agreements, and transfer pricing schemes. For instance, demand forecasting and supply network planning require the integration of information and processes across functions and regional units. If this is systematically done, it unlocks hidden synergies in manufacturing and logistics networks alike.
Physical flows captured by “digital finger prints” create improved visibility of all corporate assets. The utilization of a specific production line, truck or administrative function can be made visible with little extra cost. The major benefit of a fully digital operating model, in terms of visibility, lies within the integration of operational and financial data, which today are often separated up to a profit center level. For instance, customer orders can be evaluated against individual process costs instead of average cost. In some cases, connecting internal data with external facts, such as market share or competitor prices, can lead to meaningful new insights.
Conclusion – Approach to Digital Supply Chain Transformation
It is important that a digital supply chain strategy be an integral part of the overall business model and organizational structure of a company to generate and measure long term value. Transforming the entire organization to a digital operating model clearly has the highest potential, but also bears the highest complexity and risk. A thorough analysis phase will highlight the value creation potential, in the existing supply chain. The identification of business benefits requires top management expertise and inputs, regarding currently perceived pain points and industry best practices. Typical outcomes of an analysis of current pain points are the identification of examples of broken processes, local instead of global optimization, low visibility (for example, on product/customer profitability, or process quality) or sub- critical size of local business units. A synthesis of these pain points will lead directly to the design principles and value potential of a digital supply chain model. Model framework of digital strategy is shown in figure 3, which helps OEMs to capture missing aftermarket revenue, due to low visibility in end-to-end value chain.
Figure 3. Digitization of Supply Chain Framework
At CGN Global, we embrace digitization to reconfigure supply chains and overcome traditional geographic or functional silos. We believe that highly automated end-to-end processes, flexible bundling of activities and improved visibility are the hallmarks of a fully digital supply chain. It is more about aligning digital initiatives with supply chain goals and adopting a digital operating model to realize the untapped potential of existing resources and capabilities resulting in a higher level of performance.
The Internet of Things (IoT) is the network of physical devices, vehicles, home appliances, and other items embedded with electronics, software, sensors, actuators, and connectivity that enables these things to connect and exchange data. This creates opportunities for more direct integration of the physical world into computer-based systems, resulting in efficiency improvements, economic benefits, and reduced human exertions.
The number of IOT devices is estimated to reach 30 billion devices by 2020. The global market value of IOT is projected to reach $7.1 trillion by 2020. According to Gartner, more than half of major new business processes and systems will incorporate some element of IOT by 2020. The Internet of Things has become a hot topic across the business world, in part because of the sheer number of “things” being connected over the internet. These devices, including cars, industrial robots, washing machines, elevators or home thermostats, are being outfitted with sensors and connectivity that enable them to generate high volumes of data, and transmit via the internet to organizations on the receiving end, collecting and analyzing that data, to make a variety of decisions.
IOT is implemented in all kinds of industries, like agriculture, manufacturing, healthcare, across company-wide programs, like supply chain, smart home gadgets, and wearable devices. Amazon’s Echo (Alexa), Home Thermostat Nest , Eco Bee, Google Home, healthcare wearable devices like Fitbit, Microsoft’s Azure, connected cars like Tesla, BMW, as well as home automation and home security devices are all great examples of how IOT is implemented across industry boundaries.
The Implementation of IOT cuts cost and reduces risk and complexity associated with managing millions of connected devices in large-scale disparate environments.
How IOT is Revolutionizing Supply Chain Management
Supply chain management is a foundational business process that impacts nearly every enterprise, from manufacturer, to transportation of finished goods, to the point of sale. The following are some of the operational examples made possible through Industrial IOT and representations of IOT's impact on supply chain.
- Asset Tracking: Based on RFID tags or global SIMs allow a supply chain manager to know the real-time location of a product, truck or shipping container. Identifying, locating, and determining the status of assets is the top function of IOT.
- Better Insights into the whereabouts of shipments by using the sensors and avoid manual counting and human errors.
- Fleet Management: Companies, like DHL or Fedex, use cloud platforms that are fed data from the fleet, along with traffic models, weather reports and other sources, to plot an efficient route to deliver packages to customers.
- Network operators & Equipment Vendors: Data Analytics is a large portion of deriving supply chain efficiency from IOT. Companies like Verizon, IBM and Cisco are deriving supply chain efficiency from IOT, by establishing greater visibility into supply chain data and processes, leveraging cognitive technologies.
- Manufacturing Maintenance: One area where supply chain IOT progress can be seen is within production facilities that integrate sensor networks into machinery, to increase up-times, reduce operational cost, and improve overall quality of service. IOT - driven solutions have the ability to aid the efforts of mobile and web applications to control real-time operations and visibility by collecting data, like temperature and equipment malfunctions.
Photographic instruments can now scan machine components, such as blades, to send alerts for predictive maintenance. Additionally, scanners can check raw materials for traits like paint color, alloy strength, or fabric composition, to confirm accuracy before they are used for a finished product. Higher up-times for manufacturing can be seen in production facilities that integrate sensor networks into machinery.
Inventory Forecasting: IOT data provides critical information, changing the way manufacturing and distribution companies understand procurement operations. For instance, transit or retail stock levels can be closely monitored, including 3PL distribution centers and warehouses, so companies can receive advance warning on any shipping error, reducing data-entry errors and prolonged cycle times.
The collection of data intelligence, with pattern analysis over time, enables accurate forecasting and intervention, should faulty operations occur. As a result, inventory planners, production and procurement managers can be better informed and equipped for executive decision-making on materials to hold, build, or buy, better and more accurate forecasting; by closely monitoring retail stock levels, through more reliable connections, between assets and end users, and using IOT to get data to time an item’s shelf line.
CGN Global utilizes its predictive analytics knowledge to help businesses win in the expanding IOT space, by driving collaborative and innovative, easy to manage, adaptive supply chain networks, connecting IOT to the business, providing a fast response to dynamic markets.
We help our clients solve difficult problems and become winners in the marketplace. We do this with a powerful combination of good thinking, broad capabilities, and sheer drive to go beyond what's expected.
It's what we do - and we've been doing it for more than 20 years.
WHY IS EVERYONE GOING “IoT” ?
The Internet of Things (IoT) is the new “abracadabra” in the retail world. The technology has been around for at least 25 years, though the technology has only just matured, and is creating an impact on retail businesses.
In a recent article, Forbes reported that retail sales in 2017 were $3.5 trillion and estimated a 4% growth this year. Indeed, there is opportunity to increase revenue, by targeting the right customers, but despite increased sales, 7,000 major store closing announcements were made last year. The store closings were caused primarily due to the changing behavior of the customer, and the ease of ordering a product with the click of a button or a simple voice command. Brick and mortar stores carrying products have merely become museum pieces, a thing of the past. Retail sales are continuing to grow. However, the channel that the product is being purchased through by the customer is changing. By analyzing customer behavior and providing real-time solutions, IoT devices and applications create impact and improve operations in this pivotal shift. The change in customer behavior causes a necessary change in structure of supply chain networks and financially sustainable business models.
HOW CAN IT HELP ME?
CGN continues to recognize this shift across the retail industry. As retail supply chains continue to go more and more digital, IoT devices and applications are becoming magic wands, ready to instantly shift a supply chain’s course. With retail giants, such as Amazon and Walmart, sharing their digital transformations through IoT software, retail vendors and distribution centers, they have encouraged this shift. In the hope of growing the business and taking it to new heights, a few IoT impacts on the retail business include:
Using temperature sensors for refrigerators to set optimal temperature control for grocery productsIdentifying Target markets
Identifying substitutional, impulsive, and loyal customers; in addition to targeting them with marketing coupons and improving the journey of the customerCost Reduction
Setting the right amount of energy resources (electricity) required and predicting downtime for machinery present in retail stores
Predicting the next stock out and plan optimal amount of buffer stock; critical for perishable retail products with short shelf life
Even though IoT is cool and a hip thing to talk about in business conversations, it is important to analyze each business problem individually and estimate the true value and impact of IoT applications for each problem. In conclusion, IoT devices and applications still need to mature, in terms of creating an ecosystem of devices, analyzing real-time data, and generating a point of focus for autonomous operational use. Be careful while playing with magic.
CGN Global’s Digital Transformation Service is uniquely positioned to recognize and address this industry shift. CGN has developed digital solutions that provide business insights by leveraging the signals gathered from these IoT devices and other sources. It can help transform organizations worldwide to improve performance, profitability, and global competitiveness. We use our diverse experience and broad knowledge to provide strategic insights, actionable recommendations, and focused execution to drive results. We identify the challenges and the market opportunity with the use of IoT applications.
Companies operating globally, in a wide range of markets, cater to various needs of customers, with different requirements. This requires having the flexibility to offer a large variety of products, which increases complexity, costs, and efficiency. Companies need to develop a strategy, to manage offering these wide varieties of products, with an increased standardization of components.
Traditional product design within product life-cycle management (PLM), focuses on integrating product requirements into design, but fails to address the need for variants without increasing complexity.
Modular design is an approach that enables the standardization of components, and facilitates offering a wide variety of product
A product with modular design is created by combining standardized components or modules that can be combined in different ways. Examples of systems with modular design include buildings, computers, cars and solar panels.
Modular sourcing is a sourcing strategy that allows companies to realize supply chain efficiency gains; through procuring standardized modules or sub-assemblies from suppliers. This will require development of standardized modules, during product development, and working closely with the suppliers to ensure module development is realized. Modularity benefits span the entire supply chain, as shown in Figure 1.
Figure 1. Modularity Benefits
One of the critical aspects of modular sourcing is developing modules. Our approach to modularization of a product is defined in 5-phases as shown in Figure 2.
Phase 1: Clarify customer requirements. Understand the primary objective of the company, to pursue modularization, and learn how modularization will help the company achieve its strategy and satisfy customers. Companies need to gather the voice of the customer and the voice of the business to guarantee that they are met via modularization efforts.
Phase 2: Select technical solutions. Translate customer requirements into functional requirements. Identify functions and sub-functions necessary to meet each functional requirement and develop a functional structure. Identify product components for each function and sub-function, and develop the overall product structure. Identify interfaces between each component within the product structure.
Phase 3: Generate concepts. With the product structure defined, and interfaces identified, identify modules based on ideas from standardization and variants, assembly processes, and feedback from suppliers.
Phase 4: Evaluate concepts. Evaluate the developed modules and alternatives, based on various factors, such as cost, flexibility of changes, and level of modularization. Evaluate how modularization will help the company achieve its strategy and meet customer requirements.
Phase 5: Improve each module. Evaluate if the current level of modularization will help the company achieve its strategy and continuously improve modules until the objectives are met.
Once modules are finalized, the supplier collaboration has to continue to ensure the supplier has the necessary processes and technology developed to make the modules.
Figure 2. Modularization Approach
CGN Global has worked with clients in heavy equipment manufacturing, to address their business imperative of improving product response time to the market, have a competitive and flexible cost structure and evaluate make vs buy strategy. We assessed the internal requirements and facilitated workshops to evaluate a make vs. buy strategy, cost breakdown, product design, assembly processes and supplier footprint, and generated modularization ideas by working with various functions including engineering, manufacturing, purchasing, logistics and suppliers. Ideas were generated and project teams were established to execute ideas that include modular design and sourcing, resourcing for supplier base consolidation, assembly process improvement, and material cost reduction. Modularization efforts resulted in reducing time to market by 12%, 6% total cost reduction and 15% supplier reduction.
Mergers and Acquisitions (M&A) is a common phenomenon these days, involving consolidation of companies or assets. For instance, the recent acquisition of Broadsoft by Cisco Systems will help Cisco provide broader solutions to its clients and grow, in terms of subscribers, product portfolio, revenue, and size. It takes a lot of detailed financial analysis, and a huge negotiation process, involving many M&A firms – investment banks, law firms, accounting firms, consulting & advisory firms, before successfully sealing the deal, to perform post-merger integration activities.
After either a merger or an acquisition, there are huge opportunities to leverage through supply chain integration and consolidation, namely:
- Economies of scale
- Improved customer service
- Service / SKU / Part number conversion to improve sales
The parent company would try to make significant efforts in reducing costs and pursue one or more of the following:
- Corporate restructuring
- Supply chain integration and network optimization,
- Operational improvements to break even on acquisition costs.
When performed effectively and efficiently, a post-merger supply chain integration could lead to significant reduction in supply chain costs, which helps to breakeven on acquisition costs faster. So, the first step in performing the integration process is an assessment to understand the functions / areas that can be merged. Understand the levers that need to be considered while performing the integration. From a supply chain standpoint warehousing, logistics, systems integration, and end to end network design must be considered.
To do it the right way, a network model replicating the current state network should to be created including all products/parts, supply base, manufacturing centers, distribution centers/warehouses and logistics network of both the parent and the acquired firms. Feasible scenarios should be identified, which would bring significant improvements to the resulting supply chain network, in terms of customer service, and total supply chain costs; for instance:
- What happens to total cost when the supply chain network of the acquired is absorbed by the parent?
- What happens to supplier performance when the supply base for similar parts is resourced and/or consolidated?
- Can we significantly improve service levels by keeping some of the warehouses open from the acquired?
After validating scenario results, implementing changes to the network will be quite challenging, both from a process and physical integration standpoint.
CGN Global recently helped a heavy equipment manufacturer successfully complete the integration of its aftermarket supply chain network with the acquired firm, to improve service, sales, and cease the legacy aftermarket supply chain, as well as save millions of dollars in total annual cost. The client wanted to launch an enterprise wide aftermarket supply chain integration, to consolidate all acquired parts inventory and manage the distribution and sales, through the existing well-established and more comprehensive aftermarket network. This would lead to all benefits that were previously mentioned.
The parts integration process and team, along with our consultants, were considered a separate factory that converted and superseded legacy parts into the client’s current aftermarket supply chain. CGN was responsible for establishing the process, and improving the overall operational performance of this factory, by building efficient tools and solutions.
At CGN Global, we build fast paced, effective and efficient solutions to solve the identified root causes. Our 20 plus years of experience and expertise in problem solving, and solution building, have helped our clients successfully improve the EBIDITA, through significant reduction in total supply chain costs, by completing the integration swiftly and accurately.How do we integrate?
A blue ocean represents all industries not in existence today, as an unknown market space, untainted by competition. In Blue Ocean Strategy, demand is created, rather than fought over. There is ample opportunity for growth that is both profitable and rapid. There are two ways to explore a blue ocean.
In a few cases, companies can give rise to completely new industries, as eBay did with the online auction industry. However, in most cases, a Blue Ocean Strategy is created from within a red ocean, where a company alters its boundaries within an existing industry.
A prime example is Cirque du Soleil. By breaking through traditional boundaries, bridging circus and theater, Cirque du Soleil made a new and profitable blue ocean from within the red ocean of the circus industry.
Cirque du Soleil is a Canadian entertainment company, founded in 1984 by two former street performers, Guy Laliberté and Gilles Ste-Croix. Guy and Gilles did not restrict themselves to traditional circus, by combining the best elements of circus and theatre. In doing so, they eliminated the trade-off between value and cost for the consumers.
W. Chan Kim and Renée Mauborgne, the creators of Blue Ocean Strategy, define the four steps that Cirque du Soleil took to create a successful blue ocean. These steps are include:
Unfortunately, most companies seem stranded within their red oceans. In a recent study conducted, comprised of 108 companies, it was found that 86% of new ventures were incremental improvements to existing industry offerings. A mere 14% were aimed at creating new markets or industries. While line extensions did account for 62% of total revenue, they delivered only 39% of the total profit. By contrast, the 14% invested in creating new markets and industries, delivered 38% of total revenues and a startling 61% of total profits.
By focusing largely on competition, companies have ignored two very important lucrative aspects of strategy. One such aspect includes finding and developing markets where there is little or no competition (blue oceans). The second aspect involves exploiting and protecting blue oceans. These challenges are very different from those to which strategists have devoted most of their attention.
Leading-edge technology is sometimes involved in the creation of blue oceans, but it is not a defining characteristic. This is often true even in industries that are technology concentrated. As seen over time, across all industries, blue oceans are seldom the result of technological innovation. However, the underlying technology was often already in existence. Even Ford’s revolutionary assembly line can be traced to the meatpacking industry in America. Like those within the auto industry, blue oceans within the computer industry did not come about through technology innovations alone, but by linking technology to what buyers valued. For example, the IBM 650 and the Compaq PC server often involved simplifying the technology.
At CGN, we help our clients look past the red ocean and aim for the blue, by looking to the future, exploring new innovative and disruptive markets. We empower company leadership to look at the holistic view of industry, its customers, and visualize the current and future gaps within the industry. From here, CGN drives transformation by eliminating and reducing extra features, while raising and creating value for customers, by re-defining the organization, and turning assets into advantages, driving innovation and agility across the organization, truly transforming the business with a roadmap to the future.