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The recent natural disaster that occurred in the United States, Hurricane Michael, left destruction throughout the state of Florida. Michael is one of the strongest hurricanes to hit, based on the wind speed and barometric pressure. The damage has been immense, both in terms of lives lost and infrastructure impairment. Some of the statistics (US) are as follows:
$8 billion worth in economic damage.
4000 homes destroyed or substantially suffered damage.
10% increased transit times during the storm’s presence.
PREPARATION IS KEY
Preparing for a natural disaster helps reduce the impact of disruptions caused in a supply chain. Using digital technology and creating an ecosystem, by using IoT devices, can help mitigate risks and provide a platform for speedy recovery. Business decisions, such as supplier risk assessment and logistics networks, can be optimized by incorporating big-data analysis. Listed below are 4 vital aspects to consider while dealing with a possible disaster ahead.
Identifying and quantifying potential risk, running simulations and generating optimal mitigation plans for stores, factories, warehouses and trucking routes.
Building a digital framework of a supply chain and optimizing decisions based on big-data analysis to meet customer demand, while transferring existing inventory in the network to particular stores in disrupted regions.
Using automated systems, which analyze the data, and communicates to customers, regarding delays and supplier reduction in volumes. Analysis and automated replies can be programmed in the system in case of natural disasters.
Develop a systematic process to back up records to a digital cloud, and retrieve data post-disruption. Identify key members who will activate the plan and deploy a crisis management team for inter-operability among business lines.
AFTER A STORM COMES A CALM
Using multiple variants of “digital," listed above, one can guarantee that the pre-disaster predictions are received well in advance. As a continuum, better damage control measures are conceived and implemented. By preserving every bit of intelligence related to a supply chain on a digital platform, the revival becomes smooth; similar to re-attaching a node to the system.
CGN Global is uniquely positioned to recognize and address issues when a supply chain network is disrupted. We use our diverse experience and broad knowledge in that domain to provide strategic insights, actionable recommendations, and focused execution to drive results. We identify challenges faced when a natural disaster comes to play and help organizations mitigate the damage, by quantifying the impact, well in advance, building robust communication channels, planning inventory shipments, and finally ensuring that business continuity is preserved immediately following the disaster.
Collaborating with partners across the extended supply chain, on demand forecasting and real time demand sensing, helps stock outs in volatile market cycles
Aftermarket services are a high-margin business, and they account for a large portion of profits, especially in heavy equipment manufacturing. The biggest problem in the present-day world is the high competition and volatility of market fluctuations, causing downturns and upturns. No matter what the causes are, the effect is either going to have high backorders from customers or end with huge unsold inventory lying on the shelf. There is not a one-size-fits-all answer to solve this problem.
In recent years, many large heavy equipment OEMs experienced excess inventory levels in a downturn and stock outs in an upturn. To carry the right inventory at the right time, in the right regions, for the right customers has always been a challenge, especially during volatile market situations. Recently, one of CGNs clients had gone through a severe downturn, and as a result launched initiatives, reducing material costs and inventory, across the organization. Even before the recovery was seen, the company experienced a sudden growth in demand, which resulted in back orders.
CGN’s extended collaborative supply chain management solution, which encompasses concepts of collaboration planning, forecasting and replenishment (CPFR), as well as CGN's digital strategies have helped clients understand customer behavior, provided correct upstream forecasting signals, established end-to-end supply chain connectivity and reduced back orders, while improving service levels.
Overview of CPFR Approach
Collaborative planning, forecasting, and, replenishment (CPFR) extends vendor managed inventory principles and is the latest stage in the evolution of supply chain collaboration. Older supply chain initiatives have gaps in their practices. As in many operations, financial plans take precedence over forecasting, resulting in high inventory levels, lower order fill rates, and increased expedited activities. CPFR is a set of business processes that help eliminate supply and demand uncertainty through improved communication and collaboration between supply chain trading partners.
It also facilitates the reengineering of replenishment between trading partners. An important promise of CPFR is that accuracy of the forecast (demand, order, sales) can improve by having the customer, dealers and suppliers participate in the forecast. In general terms, buyers and sellers work together to satisfy the demands of an end customer, who is at the center of the model. Figure 1. (below) illustrates this model, which is applicable to many industries. If a discrepancy occurs, the trading partners can get together and decide on the replenishment quantity to rectify the problem. This type of collaboration offers great potential for drastically improving supply chain performance
Fig 1. Components of CPFR Model
Below are the steps taken to set a stable CPFR platform
- Develop front end agreement with trading partners
- Create joint business plan
- Create sales forecast
- Identify exceptions for sales forecast
- Resolve/collaborate on exception and critical items
- Create order forecast
- Identify exceptions for order forecast
- Resolve/collaborate on exception items
- Order generation
CPFR is not considered a technical standard. The CPFR process does not fundamentally depend upon technology. CGN’s extended solution combines process with use of technology. It advocates using common tools and processes to improve supply chain planning through accurate and timely information flow. Powering up the CPFR process with technology can make the process more scalable. The following are examples that have been developed to facilitate the process:
- Sharing of historical data and forecasts
- Automating the collaboration process and joint business plan
- Enabling revisions
- Evaluating exception situations
Collaboration is the crux of CGN’s supply chain management. Ongoing and long-term collaboration and partnership between manufacturers and dealers delivers value to customers and profitability to all collaborating partners.
Some of the critical success factors that could influence adoption of this process are:
- Top management involvement
- Trust between collaborating partners
- Continuous measurement of performance
- Innovative IT strategy
- Up-to-date cost accounting methods
- Emphasis on customer satisfaction
- Flexible organizational structure
- Proper staff training
Our experience suggests that, for the CPRF model to be successful, it is more important to align supply chain goals with digital strategies. CGN has years of experience delivering these unique solutions, helping clients achieve high performance results. At CGN Global, we transform businesses globally, by delivering the unexpected. It is through years of service and outstanding transformative solutions provided, that we believe adopting a highly automated digital operating model can establish end-to-end processes, data connectivity and improved visibility, across the board.
CGN. Good thinking. Globally.
From early attempts to make data more manageable in the 1960s with IBM’s Bill of Material Processor (BOMP), to the current software suites and other analytical tools, the procurement practice has gone through half a century of immense transformation.
1960 BOMP & DBOMP 1970s MRP 1980 MRP II 1990 ERP
With the introduction of procurement suites, sourcing and procurement professionals gained access to powerful applications and web-based tools that greatly increased their efficiency; by improving the processes, capabilities and impact on the organization. Sourcing and procurement organizations were able to move away from fax machines and phones to an automated environment that could be managed either within the application or web portal with additional integration with email tools.
Key features of these newly developed software packages included:
- Electronic RFx (RFI, RFQ, RFP)
- Reverse auction or e-auction capability
- Supplier and buyer portals facilitating the exchange of documents
- Procure to Pay (P2P)
- Internal catalogs for buying organizations
- Business intelligence and spend analysis tools
Advantage: Reduced timing RFP approach from a month to handful of weeks
While the introduction of these tools brought about a revolution, the sourcing and procurement space is evolving with the latest phase, (just as significant and impactful as the application revolution) integration.
The integration of enterprise data, procurement tools, supply base and supply chain have closed the gap enabling stakeholders, procurement and suppliers to collaborate more efficiently, becoming more strategic in all fronts.
CGN has vast cross-industry experience in strategic sourcing and procurement, as well as full systems integration. From new product introduction, to the final invoice transaction and warranty management, our work in the manufacturing, retail, insurance and finance sectors has allowed us to refine our approach, gaining unparalleled insight into best practices for best results, delivering maximum ROI faster.
While selecting the tools is an important step in the process, it does not resolve the human aspect of having the appropriate levers applied to deploy a strategy. Addressing the operational and procurement practices are critical to achieving sustainable objectives.
Once there is an in-depth understanding of the current state, the future/desired state can be developed, along with the sourcing strategy and future state supplier relationship management. After defining the desired state, a tool can be easily selected to incrementally improve organizational efficiencies and its strategic organizational posture.
Our approach to achieving our client’s objectives is proven, bold, collaborative, nimble, procurement tool agnostic and delivers the unexpected. Let us show you what the future looks like.
With roots in the early 1950s and 1960s, private equity (PE) and venture capital (VC) engagements in the U.S. and global economies in the mergers and acquisitions arena, specifically acquisitions, have steadily increased and evolved. Private equity (PE) activity took hold in the 1980s, as the U.S. and global economies accelerated, spreading itself across the globe with a significant proportion of it focused on U.S. and European markets.
PE institutions' primary objectives are focused on profitability, yield, growth and performance, where they have a proven track record. The only slowdown in the industry has been during economic downturns. Even the 2008 crisis only temporarily slowed PE investment. However, the event demonstrated a turning point and a shift in fundamental strategies incorporated by PE institutions since the 1980s.
Acquisition strategies of PE firms have evolved in a multitude of ways; in their nature as acquisitions through partnerships or as individual investment firms or other factors like the financial status, size or specialization of the acquisition under consideration. A more significant strategic change in the last couple of decades has been in the fundamental length of their acquisition ‘hold’. Initially acquisition exits, or transitions, were not common. Over 50% of acquisitions today are exited within 3 to 5 years. Until recent shifts, exits were often seen as quick as 1 to 3 years; a trend that has since subsided. The shorter time frame not only means that up front acquisition analysis must be concise and rigorous, but strategies and execution must be agile, deliberate and rapid.
As the global economy changes, some of the key reasons for change in hold periods include:
Available capital and demand for quick yield and return on investments
In comparison to the late 20th century, the volume of capital available in today’s growing economy is significantly higher (except for the 2008 crisis). Sources of capital availability include, the banking sector that has reconfigured itself to serve transaction heavy acquisitions, large pension schemes, as well as private family funds, all playing an active role in the PE space demanding strong, quick returns.
With this availability of capital and market competition with technology and health care giants, the demand for a strong and rapid return on PE firm investments has increased.
Until recently, lower interest rates have been available, allowing PE firms to take advantage of the propagation of capital availability.
Transition Arms for Corporate Spin-offs
As the public sector moves away from ‘diversified’ business models, and chooses to rapidly spin off segments, due to profitability or the need to raise capital, PE acquisitions and short-term holds have increased (e.g. J.M. Smucker, G.E. Industrial Engines). This facilitates short term PE ownership of these assets as they ‘flip’ them and transition them to another entity, or PE firm.
Strong Performance of Initial Public Offering
Whether private companies, start-ups or PE firms, the continued growth of the global economy has resulted in the strong performance of initial public offerings (IPOs). The opportunity has been taken advantage of by PE firms, as they quickly spin off well-developed assets they are invested in via a complete or partial exit.
Public Sector Strategic Acquisitions
While some public companies have spun off diversified assets, some have trended towards specialization of their core businesses; purchasing assets managed by PE firms for rapid growth (Xylem, Unilever, Crown Castle), resulting in shorter hold periods for PE firms, as these opportunities arise.
The changes in the global economy, along with these reasons, envelope some of the key factors that have created strong conditions for PE firms. As regulations and investor requirements change, the last few years have demonstrated new shifts in strategies. Additionally, increases in valuations, interest rates, concerns surrounding potential bear markets and regulatory tax code changes have resulted in PE firms focusing in on medium term acquisition hold periods. These changes often result in PE firms relying on additional resources, support and expertise, to achieve the outcomes envisioned.
Transforming businesses globally by delivering the unexpected.
PE firms move through a multi-step approach, starting with initial evaluations and planning periods prior to an acquisition, following which they move into change management, implementation, and a planned exit transition.
CGN’s capabilities align extremely well with the needs of PE firms, post-acquisition to transition or exit, especially with CGN’s core strength in rapid, agile transformations. The firm's expertise in operational analysis and improvement, execution, and value creation can play a critical role in supporting PE firm acquisitions. CGN’s core abilities, practiced solutions can support the most pressing needs that PE firms seek support in; maximizing returns, faster, making CGN the ideal strategic partner.
In current economic times, where economic cycles are shorter and volatile, companies within all industries are looking for every competitive edge. Financially, companies are looking into all aspects of the business to improve their bottom-line. Costs of renting or leasing equipment outweighs the benefit-to-expense ratio of buying and owning equipment. Business trends show an increase in equipment rental, as part of their business strategy, allowing them to conserve capital.
Looking at this trend, heavy equipment manufacturers and dealers are leaning towards rental services as a part of their product and service offerings.
According to the American Rental Association, the equipment rental market has witnessed outstanding growth in recent years. From 2016 to 2017, heavy equipment rentals increased 75%. By 2023, the total revenue is expected to be $90 billion. This poses a supply chain challenge to manage the rental fleet network.
Key challenges for rental supply chain:
- Optimize rental network: Having right set of rental locations/hubs to serve customers
- Rental fleet management: Carrying right types and quantities of rental fleet at the right locations/hubs
- Maximizing rental fleet utilization
- Increase availability to customers
- Maximize profits & minimize total costs
To be able to arrive at a solution for the challenges above, it is imperative to map and model entire rental operations and associated costs, flow of inventory (rental fleet), and customer arrivals to rental locations. This allows businesses to have a more holistic view of the problem and helps identify bottlenecks and constraints across the rental supply chain. CGN's unique methodology simulates and optimizes rental supply chain networks. One can design alternatives and explore the service, performance, costs and risks associated with change, all within a single integrated software platform.
A holistic solution, leveragin CGN's expertise and Llamasoft's Supply Chain Guru platform, helped a major rental dealer identify opportunities to consolidate its rental facilities resulting in bottom line improvement. This approach helped make decisions surrounding rental fleet management that resulted in increasing availability to customers, while maximizing the fleet utilization and minimizing idle inventory.
Below are two approaches that addressed the client's rental business challenges. These approaches identified opportunities to increase service levels by 6% and sales revenue by 7%.
Greenfield analysis to identify the right number of rental locations to serve the existing customer base.
This analysis considers the center of gravity or weight center technique, which is a quantitative method for locating a facility at the center of movement in a geographic area, based on weight and distance. In this case, total operating costs were considered as weights, where distance is physical distance from rental locations to customer locations. This analysis aided decision making around location consolidation, as well as new location additions within the rental network. These strategic decisions allowed rental locations to position themselves closer to the customer base, while minimizing the total cost of business.
Total Cost Evaluation
Fig 1. Greenfield analysis recommending optimal number of rental facilities
CGN's rental network modelling and optimization approach for better fleet management.
From a supply chain standpoint, there is a distinct difference in the way inventory flows in a rental network, compared to the flow of inventory in a manufacturing network. In a typical manufacturing supply chain, inventory is generated in a raw material form, at the upstream, and gets consumed as a finished product at the end customer point of use; a relatively straight forward flow where the model variables have a linear or a step function. However, in a rental network, there is a return loop and an average rental period, which dictates the fleet inventory and availability. It is imperative to make quantitative decisions, like how much inventory the network should hold; while minimizing total costs and improving availability. Managing the rental fleet by positioning the right inventory at the right location in a return-loop cyclic environment, is key. Deriving an appropriate objective function that considers the business objectives, including all of the above-mentioned rental constraints, is critical.
Manufacturing Supply Chain
Rental Supply Chain
Fig 2. Modeled vs. Actual Rental Inventory - recommendation on right rental fleet inventory
Consumer product companies cover a vast array of product categories and come in numerous shapes and sizes. Consumer packaged goods (CPG) are items used daily by the average consumer and need to be replaced frequently. Basic examples include: food, beverages, clothing, tobacco, and household products. Additionally, cosmetics and frozen dinners can be categorized under CPG.
There are two main characteristics of CPG. First, CPGs are meant to be consumed quickly and sold at a relatively low cost. Second, CPG companies are less likely to be affected by market fluctuations. If the future economic condition is uncertain, people are less likely to spend large sums of money on ‘durable goods’, especially when they own older version of the product. However, people will still spend a fixed amount of money on CPGs.
CPG companies are worried because traditional growth models must be changed for adjusting the magnitude and pace of change in the US market. Some CPG companies are considering leveraging ‘digital’ to leapfrog. Having said that, in a CPG business, strategic decision-making is often perplexing due to the complexity of these businesses. They could have several brands, multiple target consumer groups, operate in multiple geographic regions, various channels of distribution, and so on, which makes evaluating these decisions difficult and complex.
Challenges faced by the CPG Industry
From brand perception to supply chain efficiency, not to mention pricing, product innovation and, of course, assessing customer needs and behaviors, consumer products companies face a long list of things they must get right to survive in the ever-changing CPG marketplace.
There are three main challenges facing the current CPG industry:
- Pervasive digitization of path-to-purchase. Large CPG companies want to leverage direct-to-consumer strategies to drive cross-channel sales, profits, and consumer loyalty within the digital word. There is an increasing use of digital tools for in-store purchases. Additionally, barriers to enter the market are being overcome. Under the influence of e-commerce, traditional market and channel economies of scale dissipate. Smaller and nimbler competitors are empowered to threaten the grocery’s goliaths – Kroger, Meijer, and Schnucks, to name a few.
- Health, wellness, and responsibility as the new basis of brand loyalty. Companies might experience greater pressure to promote sales volume with satisfying consumer interests and values toward health and wellness products.
- The value of mass-production – economies of scale are being undercut by new business models based on customization and the delivery of individual units. CPG companies are struggling to further gain/realize profits from economies of scale; while they make diverse products at the same time to meet costumers’ need.
Retailers are placing smaller orders more frequently and furthermore; those retailers are asking CPG companies to deliver goods on time which are otherwise penalized for a delayed delivery.
Due to a confluence of evolving technologies, consumer demographic shifts, changing consumer preferences and economic uncertainty, stress is placed on traditional sources based on obtaining a competitive edge, such as scalability, brand loyalty, and retail relationship.
“The marketplace is facing channel disruption on a dramatic scale, growing e-commerce penetration and the continued strengthening of Amazon, new and disruptive business models, demographic shifts and renewed spending priorities, highly informed and empowered consumers, and rapidly evolving technologies.”
Also, there is a push to optimize shelf space to maximize profit, because of the more recent crunch from online markets. Additionally, large retailers are looking to hold less inventory and reduce order quantities, which in turn will lead to less frequent shipments. Therefore, inventory optimization is increasing in importance.
“The changing channel landscape is forcing many consumer brands to restructure their go-to-market strategies to drive more productivity from fewer points of distribution, and to build direct-to-consumer strategies that require capabilities and expertise that don’t typically reside in-house today.”
Many CPG firms have made the decision to upgrade packing designs to attract more buyers. More and more customers are willing to spend money on personalized products. It is the same for CPG industry even if the price is relatively low.
“Today, consumers are increasingly looking for “specialty” brands that deliver on precise needs, and thus grant brands less “permission” to expand beyond their core. The appeal of power brands has eroded, and the prevalence of private label and other value brand alternatives gives consumers many choices when they’re trading down, particularly in an hourglass economy”
CPG firms wanting to survive in an ever-changing marketplace need to adapt to better satisfy new customer interests and by offering customers personalized products, utilizing digital tools to enhance the customer experience, and by optimizing their inventory processes.
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 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. A great example of this implementation comes from an incomplete raw data-set, where the ask was to find any patterns in the data. CGN used data mining techniques, clustering and forecasting algorithms to predict the missing data; 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 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.