Despite the fact that many manufacturers have invested in enterprise resource planning (ERP) systems and supply chain management (SCM) systems, most continue to use inopportune batch reports and pesky spreadsheets to manage their operation's performance. These have proven to be inefficient and error-prone methods of supporting decision-making, resulting in a reliance on "educated guesswork" rather than on accurate dynamic analysis to align decisions with strategic objectives. For that reason, some innovative enterprise software vendors intend to do the same for manufacturing and operational decision-making as has already been done to financial decision-making by some business intelligence (BI) applications. (See Financial Reporting, Planning, and Budgeting as Necessary Pieces of EPM).
Manufacturers today need to react quickly in order to remain efficient and competitive, given that the biggest problem they face is that change is the only constant in manufacturing. For those who are lucky, only minor changes will happen between the "as planned" and "as executed" worlds. These changes are the usual minor but endless variances that exist between planning and forecasting in the "ideal world" and manufacturing in the "real world." For all the investments spent on sophisticated supply chain planning (SCP) and manufacturing-planning tools, almost proverbially, the only sure thing about a forecast is that it will be wrong, by and large. Years ago, in business, many minor variations could be ignored as margins were sufficient to accommodate many suboptimal decisions or manufacturing processes, such as keeping increased safety stocks or frequently expediting. But in today's world of often razor thin margins, the variances between plans, real customer demand, and forecasts must all be spotted, and manufacturing success can be determined by the speed and effectiveness of the response to even minor changes.
Sometimes, however, the more serious changes, which disrupt routine tasks of planning and forecasting, manufacturing, delivering, and invoicing standard orders, result from significant unplanned events that occur either within the company or elsewhere throughout the extended supply chain (e.g., a supplier is late, supplies are wrong or of unacceptable quality, a manufacturing line is still unexpectedly busy or is down, there is a last-minute order change, etc.). The risks can be high, ranging from lost margins to loss of customers or erosion of competitive market positioning. Speed and effectiveness in response to these changes can determine the difference between profit and loss in manufacturing an order, or they can determine margin size in a manufacturing cycle or run.
In addition to the above minor and major changes, manufacturers face a third and typically more powerful change to the business itself. Namely, to remain viable and prosper in today's ruthlessly competitive global markets, manufacturers must continually reinvigorate themselves and even occasionally reinvent themselves. Fundamental business changes range from new product introductions and promotions to new corporate goals and objectives; to new target customers, continually changing customer demands and new supply chain partners; and even through to merger and acquisition (M&A) activities and structural changes to the business itself.
Some manufacturers try to cope with possibly the most difficult yet pervasive of all forces in business—never ending change—by trying to leverage the strategic information systems they have been using to control, manage, and optimize the "as executed" state of their business, such as ERP systems, or SCE systems available respectively from their ERP vendors and a broad array of pure play SCE players. However, it has been extremely difficult for them to deal with day-to-day events in real-time with a transaction-based ERP system that relies on batch processes to extract the data they need. It can be daunting for a manufacturer to get real-time notification of a supply chain event, understand its impact, and take the appropriate action given traditional ERP and or execution applications do not really provide this capability. Almost every enterprise has huge volumes of information flowing through their enterprise systems, but only few possess the tools to quickly exploit their wealth of data and thereby optimize their operational and corporate performance.
Most manufacturers will have gone a step further in addressing this problem by deploying some level of strategic planning or forecasting systems to help them forecast and model the "as planned" state, in solutions ranging from a variety of business intelligence tools, such as Cognos, Hyperion, SAS, or Business Objects, all the way through comprehensive SCM solutions, such as those from Manugistics or i2 Technologies, or again from their ERP providers. If one considers traditional business intelligence tools, they merely do a prodding analysis of historical data after the fact, but one cannot count on the future to look like the past, which has been the shortcoming of some forecasting methods as well. Therefore, more up-to-date information is a requirement.
On the other hand, best-of-breed SCP solutions may not be the answer, as they require a significant investment in both software and integration. Sometimes the solutions to improve manufacturing effectiveness are so complex and costly that they overwhelm any benefits that they might provide, such as when engaging consultants to, for example, scrutinize modeling revenue, cost, and supply chain capabilities, with breaking products into families and analyzing the channels they are sold through and the geographies they cover. Frequently, the exorbitantly high cost and complexity keeps companies from realizing the potential benefits that these systems promise.
Additionally, there are still significant barriers to an easy deployment of SCP systems, as they are based on cumbersome proprietary algorithms and heuristics that take a long time to master and harness to work, forcing companies to have full-time �rocket-science' expert consultants on the premises to interpret the results and to keep the application in tune with the business processes it supports. Therefore, the use of a traditional APS method that is non memory-resident and latent in itself, as a basis for all decision-making, is becoming increasingly unsound. Due to the growing visibility of supply chain information, the necessity of SCM has also progressively become more the provision of real-time information. Still, early supply chain event management (SCEM) systems, while crucial to increase visibility and raise flags, have lacked the ability to figure out resolution processes in the applications and their subsequent impact on operations.
Manufacturers today need to react quickly in order to remain efficient and competitive, given that the biggest problem they face is that change is the only constant in manufacturing. For those who are lucky, only minor changes will happen between the "as planned" and "as executed" worlds. These changes are the usual minor but endless variances that exist between planning and forecasting in the "ideal world" and manufacturing in the "real world." For all the investments spent on sophisticated supply chain planning (SCP) and manufacturing-planning tools, almost proverbially, the only sure thing about a forecast is that it will be wrong, by and large. Years ago, in business, many minor variations could be ignored as margins were sufficient to accommodate many suboptimal decisions or manufacturing processes, such as keeping increased safety stocks or frequently expediting. But in today's world of often razor thin margins, the variances between plans, real customer demand, and forecasts must all be spotted, and manufacturing success can be determined by the speed and effectiveness of the response to even minor changes.
Sometimes, however, the more serious changes, which disrupt routine tasks of planning and forecasting, manufacturing, delivering, and invoicing standard orders, result from significant unplanned events that occur either within the company or elsewhere throughout the extended supply chain (e.g., a supplier is late, supplies are wrong or of unacceptable quality, a manufacturing line is still unexpectedly busy or is down, there is a last-minute order change, etc.). The risks can be high, ranging from lost margins to loss of customers or erosion of competitive market positioning. Speed and effectiveness in response to these changes can determine the difference between profit and loss in manufacturing an order, or they can determine margin size in a manufacturing cycle or run.
In addition to the above minor and major changes, manufacturers face a third and typically more powerful change to the business itself. Namely, to remain viable and prosper in today's ruthlessly competitive global markets, manufacturers must continually reinvigorate themselves and even occasionally reinvent themselves. Fundamental business changes range from new product introductions and promotions to new corporate goals and objectives; to new target customers, continually changing customer demands and new supply chain partners; and even through to merger and acquisition (M&A) activities and structural changes to the business itself.
Some manufacturers try to cope with possibly the most difficult yet pervasive of all forces in business—never ending change—by trying to leverage the strategic information systems they have been using to control, manage, and optimize the "as executed" state of their business, such as ERP systems, or SCE systems available respectively from their ERP vendors and a broad array of pure play SCE players. However, it has been extremely difficult for them to deal with day-to-day events in real-time with a transaction-based ERP system that relies on batch processes to extract the data they need. It can be daunting for a manufacturer to get real-time notification of a supply chain event, understand its impact, and take the appropriate action given traditional ERP and or execution applications do not really provide this capability. Almost every enterprise has huge volumes of information flowing through their enterprise systems, but only few possess the tools to quickly exploit their wealth of data and thereby optimize their operational and corporate performance.
Most manufacturers will have gone a step further in addressing this problem by deploying some level of strategic planning or forecasting systems to help them forecast and model the "as planned" state, in solutions ranging from a variety of business intelligence tools, such as Cognos, Hyperion, SAS, or Business Objects, all the way through comprehensive SCM solutions, such as those from Manugistics or i2 Technologies, or again from their ERP providers. If one considers traditional business intelligence tools, they merely do a prodding analysis of historical data after the fact, but one cannot count on the future to look like the past, which has been the shortcoming of some forecasting methods as well. Therefore, more up-to-date information is a requirement.
On the other hand, best-of-breed SCP solutions may not be the answer, as they require a significant investment in both software and integration. Sometimes the solutions to improve manufacturing effectiveness are so complex and costly that they overwhelm any benefits that they might provide, such as when engaging consultants to, for example, scrutinize modeling revenue, cost, and supply chain capabilities, with breaking products into families and analyzing the channels they are sold through and the geographies they cover. Frequently, the exorbitantly high cost and complexity keeps companies from realizing the potential benefits that these systems promise.
Additionally, there are still significant barriers to an easy deployment of SCP systems, as they are based on cumbersome proprietary algorithms and heuristics that take a long time to master and harness to work, forcing companies to have full-time �rocket-science' expert consultants on the premises to interpret the results and to keep the application in tune with the business processes it supports. Therefore, the use of a traditional APS method that is non memory-resident and latent in itself, as a basis for all decision-making, is becoming increasingly unsound. Due to the growing visibility of supply chain information, the necessity of SCM has also progressively become more the provision of real-time information. Still, early supply chain event management (SCEM) systems, while crucial to increase visibility and raise flags, have lacked the ability to figure out resolution processes in the applications and their subsequent impact on operations.
No comments:
Post a Comment