The Sense-and-Respond Enterprise

by Grace Lin, Steve Buckley, Heng Cao, Nathan Caswell, Markus Ettl, Shubir Kapoor, Lisa Koenig, Kaan Katircioglu, Anil Nigam, Bala Ramachandran and Ko-Yang Wang

Over the past three decades, operations research groups within the IBM Research Division have conducted numerous analytic studies and developed many applications across the global IBM enterprise [1,2]. These studies have addressed strategic value chain decisions such as global manufacturing and distribution network design, demand forecasting, capacity planning, inventory management, supply planning and allocation, production scheduling and business process analysis. During the last decade, IBM Research has extended its model of research to include work with IBM's customers. Bringing IBM scientists and customers together to tackle real-world business problems has advanced the application of information technology as well as the underlying science and mathematics.

The unique role that IBM Research plays between the research world and the business world allows it to observe, participate in, and initiate leading-edge value chain design. In recent years the Internet has made a huge impact on value chain design. This impact is manifested in a variety of trends, including:

1. Customer behavior. Largely due to the Internet, consumers are becoming more informed and demanding. Retailers are no longer pushing into the market. Consumers are pulling what they want, when they want it. Increasingly, consumers value convenience over loyalty. In order for retailers to stay competitive, they must go to where the consumers are, which may be through e-commerce.

2. Collaboration. The Internet has changed the way that companies connect with customers, partners, dealers and employees. The Internet enables a shift from isolated business processes toward a more collaborative model. For example, the Collaborative Planning, Forecasting and Replenishment (CPFR) consortium has developed a set of business interactions that participants in a supply chain can use for collaboration on a number of buyer/seller functions [6]. More than $1 trillion in finished goods is in inventory in U.S.-based stores, distribution centers and manufacturing plants according to a report published by Syncra Systems Inc. If trading partners had better visibility to each other's inventory and plans, much of this inventory would not be necessary [7]. Another aspect of collaboration is that small- and mid-size companies will be able to integrate their processes and competencies to form virtual enterprises—enabling them to compete with much larger companies.

3. Service velocity. Internet communication mechanisms such as Rosetta Net [8] speed orders through the supply chain at incredibly high rates. Advances in e-business and information technology such as high information capacity, deep computing, pervasive devices and integrated business processes provide new opportunities for improving business performance based on real-time business and market intelligence. More important than the actual increases in velocity are the expectations that instant access and instant results encourage in both consumer and business users. The downside of this trend is that the current business environment is changing at an unprecedented pace. Profitable business areas can suddenly evaporate, creating tremendous challenges for resource and business optimization.

4. Product velocity. The expectation of rapid change coupled with real technological advance drives a rapid turnover of products. The profitable selling lifetime of a particular PC configuration can be as low as six weeks for example.

5. Flexibility. E-marketplaces offer businesses significantly increased options in the selection of suppliers and customers.

6. Globalization. For global companies the Internet represents an opportunity to optimize across geographies, plants, shipping costs, labor, tariffs, processes and customers. This amounts to a substantial increase in market scope that may drive some products to a commodity basis and open up markets for niche products.

The net impact of these trends presents a serious challenge to current value chain control and management systems.

At the core of current systems are the supply and demand planning systems shown in the top layer of Figure 1. Typically supply planning is focused on critical long lead-time components (some semi-conductor components may have six month lead times, for example). Driven by the long horizon, demand planning becomes a lengthy process focused on long-term risk-reward scenarios. The resulting control system, while updated periodically, relies on a fixed production target (build to plan) mechanism that is unresponsive to the rapid to medium term shifts in either market or supplier behavior that characterize the current environment.

Figure 1: A new layer between value chain planning and value chain execution is needed.

In a traditional "make-and-sell" model, there is no further response mechanism: product is built according to the plan and sold from inventory. Short-term fluctuations are buffered by maintaining adequate inventory.

One response is to drive the bottom layer of Figure 1 toward real-time operational control. Two types of systems are emerging in this area: inventory optimization that controls manufacturing coupled with short-term procurement based on inventory set points, and event monitors that give early warning of "real time" market events. A key issue with these techniques is how real-time decisions can be made in a consistent manner with planning decisions.

At IBM Research our approach is to define an intermediate layer as shown in Figure 1. Our approach, the Sense And Respond (SAR) Blue Enterprise, is a shift from the traditional make-and-sell business management philosophy to incorporate an adaptive enterprise model. Sense-and-respond organizations do not attempt to predict future demand, but focus on identifying customer needs, new opportunities and supply trends at the time scale on which they are changing [4].

Make-and-sell organizations are characterized by low frequencies of sensing and responding processes, enabled by centrally planned organizations. Adaptive organizations are characterized by high frequencies of sensing and responding processes, enabled by decentralized organizations. Although suitable for dynamic environments, the adaptive enterprise model does not take advantage of the efficiency of analytical planning and optimization—a strong point of the make-and-sell model.

An organization need not be either make-and-sell or adaptive. For example, an organization could have a high-sensing frequency and low-responding frequency. Such an organization would possess damping characteristics and might be slow to respond to external changes. However this damping effect could have a stabilizing effect on the system, rejecting high-frequency noise. This could be advantageous considering the high burnout rate in Internet companies, which emphasized the speed of response [5].

Traditional value chain management systems are based on static, structured information within a rigid planning cycle, while SAR Blue Enterprise orchestrates dynamic, structured and unstructured information within a continuous, adaptive event-based planning process. Traditional value chain management focuses on supply chain planning and execution, while SAR Blue Enterprise not only performs supply chain planning but also determines business rules and policies. Traditional value chain management responds to environmental changes reactively while SAR Blue Enterprise utilizes a real-time, predictive and proactive modeling capability.

Under the SAR Blue Enterprise model, an enterprise's key competitive advantages will be determined by its ability to plan enterprise resources carefully, establish flexible capability networks and utilize analytical analysis to maintain efficient value chains which deliver customer solutions and values. A SAR Blue Enterprise can sense a multitude of changes in the business environment, such as market conditions and operational issues, faster than competitors and before issues becomes problematic. A SAR Blue Enterprise can formulate smart responses by adjusting policies, strategies, processes and operations. It can execute those responses with speed and determination.

Enabling the transformation from a make-and-sell enterprise to a SAR Blue Enterprise requires gaining strong commitments from senior executives to transform fundamental business models, enabling processes and empowering staff to make necessary changes. The organization must establish a technological capability to process a large amount of information and quickly interpret trends and changes in the business environment. It must also build a decision-support capability to enable executives and staff at all levels of the organization to respond effectively to the changing needs of the business.

The Sense and Respond Blue Enterprise

A successful sense-and-respond system has to employ careful planning as well as intelligence, flexibility and responsiveness in execution. Additional analytical capabilities are needed to enhance a pure sense-and-respond model that may fall into chaotic situations and may not achieve high levels of distributed efficiency. The SAR Blue Enterprise is designed to address this need. It is a hybrid of the sense-and-respond and the make-and-sell model. It combines analytical data mining, planning and optimization technologies and follows an adaptive sense-and-respond philosophy with a capability to detect and use the most appropriate management policies in a given business context. This hybrid and adaptive model enables the enterprise to utilize the best model for efficiency and responsiveness under different situations and achieve a balanced business performance.

The SAR Blue Enterprise is an autonomic integrated management system driving planning and execution in alignment with strategy and business objectives through its sensing, responding and analyzing capabilities. It is an enterprise management paradigm that enables automatic sensing of complex internal and external business environmental changes, and responds quickly with the best available policies in order to achieve the business objectives. The goal is to create a digital brain with sensors reaching all the way from a company's global value chain to the Internet world, identifying, monitoring, organizing and analyzing critical business information with intelligent decision-making capabilities in order to generate and activate proper business rules, policies and processes.

The SAR Blue Enterprise model provides a flexible business framework supported by an advanced technology architecture that utilizes value chain optimization technologies. It provides enterprises with a unified platform that integrates strategy, buy-and-supply, make and sell-and-support functions into an adaptive value chain that is smart in responding to events. It enables enterprises to utilize supply chain partners' capabilities effectively so as to rapidly create value for customers and convert opportunities to revenues. It helps the enterprise to reduce costs by having better forecast and planning, adaptive execution, and by dynamically assigning resources and capabilities to areas that will have the greatest impact. It provides a platform that enables quick and cost-effective development of sensing, mining, planning, analysis, relationship management, procurement and support technologies for new partners in the global value chain. Through this framework, enterprises can build better and more tightly integrated business processes, more flexible capability networks, and a business structure that is more responsive to internal and external environmental challenges.

SAR Blue Enterprise Intelligent Agents

The SAR Blue Enterprise addresses the full spectrum of supply chain event management (SCEM), which is an attempt to integrate event monitoring, simulation and optimization capabilities to improve the supply chain control [3]. SCEM provides visibility of supply chain events, prioritization of exceptions and issuing of exception alerts to help make timely business decisions at a tactical and operational level.

The SAR Blue Enterprise takes SCEM several steps further. It integrates value chain planning with a dynamic sense-and-respond control model, utilizing an agent-based framework that supports different business and execution models. It allows enterprises to adaptively use the most effective model to address their value chain needs. Further, it helps realize operational business designs through business process integration, automation technology and Web services, and helps partners to integrate their processes and optimize supply chain collaboration.

Integrating advanced mining and forecasting techniques enable enterprises to sense trends for longer-term capability networks planning, and to sense events for short-term response optimization. And, most importantly, utilizing analytic techniques for risk management, dynamic pricing, strategic sourcing, inventory management, etc., enables intelligent decision-making and prediction of future supply chain performance (Figure 2).

Figure 2. SAR Blue Enterprise Agent Infrastructure and Coordination.

The SAR Blue Enterprise decision intelligence and risk management capability comprises a set of response agents that are selected, either automatically or by the business owner, based on a triggering sense monitor. Real-time data and information gathered from monitors is used as input to the response agent, which in turn generates results that support informed supply chain decisions. The response agents analyze the relationships between customer demand, product manufacturing, product sourcing and generate proactive policies that help optimize profit and balance profit risk. The SAR Blue Enterprise model utilizes the notion of portfolio management in every business process, from supplier management, contract management, customer management, etc., trading off risk and reward and optimizing the tactical and operational drivers in the value chain.

The SAR Blue Enterprise model covers four categories of response agents as illustrated in Figure 3. From a buy-and-supply perspective, the response agents enable better forecasts and flexible risk management, therefore greatly reducing the risks. Improved partner management and risk sharing further simplify buy-and-supply activities, and allow companies to focus on collaboration with their partners to gain support with minimal risks. From a make perspective, flexibility and better forecasts enable dynamic risk management and partner value analysis, thus increasing flexibility and decreasing response times. From a sell-and-support perspective, the response agents enable enterprises to optimally plan product offerings and sales, optimize channels strategies, as well as make quick, informed decisions about changing market demand. Dynamic pricing capabilities enable companies to flexibly set the price to optimize profits. Finally, the enterprise agents support the allocation of resources to different enterprise activities, considering the risk and return of the activity and its strategic importance to the business.

Figure 3. SAR Blue Enterprise Decision and Risk Management Intelligence.

The technologies and key innovations that support the SAR Blue Enterprise can be summarized as follows:

- Ability to detect, organize and analyze pertinent information and sense critical business conditions.
- Filters for enterprise data to enable stable responses to disturbances in the business environment.
- Intelligent response agents that analyze global value chain relationships and information, and derive the optimal strategy for the best supply chain performance.
- Predictive modeling at multiple levels—strategic, tactical and operational.
- Agent coordination mechanisms at multiple levels—strategic, tactical and operational.
- Capability to learn by comparing previously redicted trends with recorded data and information, in order to improve future responses.
- A software infrastructure to integrate heterogeneous and collaborative agents implementing critical business policies and making operational decisions. We have developed a proof-of-concept SAR Blue Enterprise system, and are conducting pilot installations at IBM business units. Our objective is to further advance IBM's leading position in supply chain management. Can SAR Blue Enterprise help us achieve this goal? Although we believe this is a significant first step, there are many more challenges that enterprises must address. Specifically, the following aspects of managing a global value chain need to be further researched:

- What are the major performance drivers of the global value chain for the new generation e-business?
- What new value propositions can be generated using new e-business technologies?
- How do the dynamics of partnerships, contracts, collaboration, global environment and value proposition impact supply chain management and design?
- How do enterprises form and manage a virtual supply chain?
- What is the role of outsourcing and contract manufacturing in the virtual supply chain?
- What requirements do virtual supply chains place on business management and IT systems?
- How does a company perform dynamic optimization with near-zero planning cycle time?
- How should a company use holistic techniques to address such issues as metrics and measurements, risk management, portfolio balancing, (dynamic) pricing strategies, routes to markets, dynamic adaptation of contract mix, "shock" response, etc.? Be sure to read the Sense & Respond Business Scenarios sidebar


- B. Dietrich, N. Donofrio, G. Lin, and J. Snowdon, "Operations Research Delivers Business Value to IBM," OR/MS Today, June 2000, pp. 52.
- "IBM's Supply Chain Gang Saves Company $750 Million," OR/MS Today, June 1999, pp. 55-57.
- J. Suleski, C. Quirk, "Supply Chain Event Management: The Antidote for Next Year's Supply Chain Pain," AMR Research, September 2001.
- S. Haeckel, "The Adaptive Enterprise—Sense & Respond," Harvard Business School Press, 1998.
- M. Bates, S.S. Rizvi, P. Tewari, and D. Vardhan, "How Fast is Too Fast?" McKinsey Quarterly, Vol. 3, 2001.
- Collaborative Planning, Forecasting and Replenishment,
- M. Johnson and T. Carroll, "The CPFR Value Proposition," Syncra Systems Inc., Waltham, Mass.
- Rosetta Net,

Grace Lin is a senior manager of Supply Chain and Business Optimization at the IBM T.J. Watson Research Center. Steve Buckley is a manager of Supply Chain Analysis. Heng Cao, Nathan Caswell, Markus Ettl, Shubir Kapoor, Kaan Katircioglu, Anil Nigam and Bala Ramachandran are research staff members in the Department of Supply Chain and Business Optimization. Lisa Koenig is a director of Supply Chain Reengineering in IBM Integrated Supply Chain, and Ko-Yang Wang is a distinguished engineer in IBM Global Services.