Globalization, consolidation, RFID and the rapid growth of big box retailers are clear indicators that traditional modes of operation will no longer suffice.
Virtually all markets are under pressure to meet the changing demands of their customers. In the food and beverage industry these demands are not only coming from the end consumer, but also from distributors and retailers who are placing their own demands on manufacturers in the form of VMI (vendor managed inventory), RFID tagging, and custom packaging. Trying to predict what the market will demand based on data that is several months or even one month old will no longer suffice. To successfully meet these demands, food and beverage manufacturers must migrate to a real-time performance management (RPM) model, where demand is tracked daily, if not hourly, to enforce a pull-based supply chain rather then the traditional push model.
A focused program of continuous improvement that drives an organization toward exceptional performance is mandatory. Maintaining that competitive advantage, however, requires monitoring of performance as well as scanning the environment for changes in what customers want and what competitors are doing.
To address these issues, ARC Advisory Group introduced the Operational Excellence (OpX) model in 2002 as a rational process for achieving competitive advantage. OpX drives the enterprise to consistently do the right things well. Real-time Performance Management extends OpX by continuously identifying goals and targets that will ensure success. RPM also addresses the challenges of today's dynamic markets where the right thing can change at a moment's notice. By integrating real-time visibility, agility and speed into the performance management system, the enterprise remains on course by knowing where it is and where it has to go.
ARC’s OpX Model drives the enterprise to consistently do the right things well. Source: ARC Advisory Group.
The real world
Managing a modern organization is complex. To succeed, C-level executives must identify the best strategies for their companies and create Real-time Performance measures and performance targets that will drive the organization to achieve these outcomes. These strategies are transposed to various operating groups within the organization to set performance targets based on their specific roles.
Traditionally, companies developed such strategies on an annual basis where assumptions are made about future demand, and pricing for products and historical information from financial systems is used to establish production capacities and costs. Strategies and performance targets were developed to optimally use the company's resources to generate profit from projected market conditions. Actual performance was measured in real-time against performance targets.
This process has several basic weaknesses. First, goals set for the company can be too conservative. Rather than focusing on the optimum performance that could be achieved, companies accept past performance as a measure of capability and focus on improvement from this position. Second, financial systems do not support the fidelity and granularity needed to understand costs and profit potential at the operational level. They implicitly include historical values for key factors such as materials and operating efficiencies. Likewise, they aggregate all products and customers, hiding such things as bottleneck effects and special services.
The conventional process is also static. While mid-course corrections may be made, such corrections are generally tactical. The overall strategy is considered sacrosanct until the next planning cycle, even if the company is rapidly going in the wrong direction. In today's dynamic world, assumptions about demand and price level rarely come true. Competitor actions such as the introduction of new products, new pricing strategies and promotions can completely change the basis of competition. Assumptions about costs and capacities likewise change rapidly. Raw material pricing can be affected by climate and political events. Equipment failures can shut down production lines, changing the cost basis and capacity for popular products.
While dynamic markets highlight the limitations of conventional performance management systems, the problems are basic to the approach and affect companies in all industries. Financial systems, which provide basic planning information, are designed to aggregate data over long time periods to satisfy reporting needs, not to run the business on a day to day basis. Company profits are generated at the wellheads, and in manufacturing there are wellheads in the sales offices, at the engineer's desk, on the shop floor, in the shipping office, in the distribution warehouses and at the customer's dock. Decisions must be made at these points on a continuous basis to keep the business going.
Static guidelines severely limit options. Discounting a product that is already unprofitable is bad for business, even if it satisfies sales volume targets based upon old pricing levels and costs. Promoting aggressive delivery times to give the company a competitive advantage can be counterproductive when production capacity is limited by unplanned equipment failures.
Effective performance management requires real-time collection of information on internal performance, market requirements and competitor activities. Internally, business systems must be tightly integrated with automation systems to ensure that significant deviations in line performance, quality and cost are immediately known in all departments from sales and planning to the CEO's office. Interaction with customers must be collaborative and real-time to immediately detect changing preferences and new competitive challenges. Suppliers and partners must be managed analogously for changes that can affect cost and delivery commitments. Constant vigilance of competitor actions is equally important and demands real-time dissemination and response.
High-fidelity models that operate in concert with real-time data collection processes are fundamental to RPM. Today's manufacturing world is simply too complex for simple analysis, yet requires proper responses. Models empower the company to project the full impact of changes on performance and can support rapid what-if analysis to evaluate tactical and even strategic adjustments that will keep the organization focused. Most large manufacturers already possess good operational models. Integration of their output with high fidelity financial models should be a paramount concern to augment and extend the benefits of more granular data.
Each manufacturer must assemble its own RPM solution based up fundamental building block to meet specific operational goals. Source: ARC Advisory Group.
One of the major benefits of RPM is the ability to utilize real-time costing information to improve performance. For manufacturing centric operations, plant automation and information systems already collect, process, and store thousands of real-time measurements that can provide the basis for real-time costing calculations. For instance, data from sensors that measure process variables such as flow rates, temperatures, and pressures for process control can also be used by process models to determine the production and cost performance of the plant on a real-time basis. This approach allows companies to monitor the performance of every process unit along with the entire plant in real-time during production. Performance values derived in real-time can be used by process operators to improve current performance of the plant and passed to higher level enterprise planning systems to improve future resource allocation decisions.
One of the biggest challenges for RPM is to identify the best ways to use this information effectively and to relate derived values to performance targets that can drive the most profit. Information must be put into the right context, integrated with the right content, and delivered to the right contact within the production cycle so that actions can be taken to improve plant performance.
Many components must come together to make RPM work. They are available to every manufacturer and many are currently in use today, but rarely in an integrated fashion that supports RPM. The challenge is that each manufacturer must assemble its own RPM solution based up fundamental building block to meet specific operational goals.
Technology is essential to any real-time strategy. Without technology, it would be impossible for operations to understand and react to conditions in today's manufacturing environment. To achieve RPM, the infrastructure must be able to facilitate all the other components that make up RPM. Since RPM is about reacting to change, the infrastructure must make that easy for all involved: operators, supervisors, engineers, as well as the architects of the specific RPM implementation.
Models empower the company to project the full impact of changes on performance and can support rapid what-if analysis to evaluate tactical and even strategic adjustments that will keep the organization focused. Source: ARC Advisory Group.
For RPM to work, workers need to see what is happening. In the context of RPM, the way information is presented takes on an even more important role. With literally tens of thousands of potential points of information that could be presented to operators and supervisors, the issue of what is presented and how it is presented is key to making real-time decisions that positively affect performance. RPM visualization must present the right information at the right time so that informed decisions can be made.
The term KPI (key performance indicator) is often defined as performance targets given to individuals or organizations indicating how performance will be measured. Unfortunately, it also has the connotation of being an annual target that is not adjusted very often. In the RPM world, targets must adapt to meet business situation.
The old saying is true: You cannot control what you cannot measure. Measurement in the context of RPM includes production, inventory, quality, and other information that is normal for operators to see and act upon. It also includes information in the context of business performance. The important RPM measurements for the operator and supervisors to see are the KPIs to which the operation is being held accountable. The closer these measurements are to true measures of business performance, the more likely operators will make the correct adjustments. The key to these types of measurements is their real-time relevance. Often, a KPI will require current values for cost, price, or market information to allow the appropriate performance measurement to be made available in real-time.
Control has a different meaning at the plant floor than at the executive level. As an important component in RPM at the operations level, the function of control is to recognize deviations from the target and make corrections to the process in real-time. The objective at the plant level is to make this action as automated as possible. Often a specific automated control function can be identified as the key component for a specific KPI. For example, a KPI for quality may be managed by a single control loop. In more complex production, however, the control function may be a combination of human procedures and automated equipment.
An integral part of determining the proper real-time response to changing operational conditions is an analysis of the business impact. Analysis may be as simple as recognizing that the situation has changed and the response may be obvious.
Analysis in the context of RPM means questioning the status quo. Just because a response to a change worked in the past, it might not be the proper response in light of the latest business situation. For example, a product may not make the profit expected if sustained operation in the current range causes production faults (e.g., catalyst deactivation, premature equipment failure, etc.).
Another critical component that is often overlooked is the prediction of where performance is headed. In operations, it is very important to know when you make a correction that it will take you in a direction that improves performance. For some operations to accomplish this, complex models that are often also used to optimize the process will be required. Sometimes the prediction can be implemented with simple mathematics. In all cases, it must result in a reasonably correct indication or operators will stop relying on it as a guide.
Knowledge in the RPM context is both human expertise as well as the captured knowledge in automated and semi-automated processes. Often the best production run can be directly linked to the best operators or workers on duty at the time. Knowledge and analysis of that knowledge are key components to moving ever closer to the goal of operational excellence.
Dynamism continues to increase in virtually all industry sectors. In the food and beverage industry, the need for RPM has never been greater. Globalization, consolidation, customization, RFID and the rapid growth of big box retailers are clear indicators that traditional modes of operation will no longer suffice. Adopting an RPM strategy and supporting infrastructure will be critical to maintaining a competitive edge in the years to come.