As we discussed in previous blogs, having a vision of the future is important to help coordinate SCM initiatives towards the “global good” – but having a vision is worthless without effective work in the trenches. The “vision” sense and respond, SAR, is as relevant now as in the year 2000. Traditional value chain management systems are based on static, structured information within a rigid planning cycle, while SAR 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 not only performs supply chain planning but also determines business rules and policies as well as formulate smart responses by adjusting policies, strategies, processes, and operations.
As we discussed in previous blogs, having a vision of the future is important to help coordinate SCM initiatives towards the “global good” – but having a vision is worthless without effective work in the trenches. One of the “vision” themes I recently heard was “self-healing”. In fact, a far better vision is “sense and respond” SAR which moves an organization from a big bang paradigm periodic driven approach that currently dominates SCM even in best in class organizations to an “as needed” basis. Although sense and respond sounds as if it is a 2020 initiative by McKinsey and Company, the original term and work were done in the late 1990s and early 2000s by the MS/OR SCM pioneers. The following discussion pulls selected items from this work. In a future blog, we will examine “Next Generational Supply Chain Optimization” by another MS/OR SCM pioneer Dr. Harpal Sing.
Some Factors Driving This Evolution
Customer behavior. 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.
Collaboration. Companies now connect on-demand with customers, partners, dealers, and employees. This drives a shift from isolated business processes toward a more collaborative model.
Service velocity. Communication mechanisms now speed orders through the supply chain at incredibly high rates and advanced computing provides 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.
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.
Flexibility and Globalization. Today businesses have “substantially more” options for the selection of suppliers and customers. With additional options comes the challenge of optimizing across a more complex demand-supply network.
Current Big Bang Approach
Typically supply planning is focused on critical long lead-time. 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.
In a traditional “make-and-sell” model, there is no further response mechanism: the product is built according to the plan and sold from inventory. Short-term fluctuations are buffered by maintaining adequate inventory.
The response is handled with narrowly focused 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.
In the current best in class approaches, there is a centralized process that drives such mainstays as demand planning and central planning (aka the big bang) an essentially ad hoc process for real-time or relevant time response from the back of the envelope calculations to simple logic involving soft pegging. The challenge is how to respond in a manner consisting of the planning decisions and avoiding “over” or “under” reacting. This the same challenge faced by “self-healing”, although at this point self-healing has yet to recognize this for the most part.
The authors, all from IBM Research, proposed an intermediate layer between the “plan” and “the response”. 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.
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.
Traditional value chain management systems are based on static, structured information within a rigid planning cycle, while SAR 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 not only performs supply chain planning but also determines business rules and policies. Traditional value chain management responds to environmental changes reactively while SAR utilizes real-time, predictive, and proactive modeling capability. A SAR driven SCM can formulate smart responses by adjusting policies, strategies, processes, and operations. It can execute those responses with speed and determination.