increased. One of the survey questions was:
How would you describe the complexity of your company’s supply chain in the last decade?
| a. Stayed the same | 15.4% |
| b. Complexity has increased | 78.2% |
| c. Complexity has decreased | 6.3% |
The circumstances under which Orlicky and his cadre developed the rules behind MRP and surrounding techniques have dramatically changed. Customer tolerance times have shrunk dramatically, driven by low informational and transactional friction largely due to the Internet. Customers can now easily find what they want at a price they are willing to pay and get it in a short period of time.
Ironically, planning complexity is largely self-induced in the face of these shorter customer tolerance times. Most companies have made strategic decisions that have directly made it much harder for them to effectively do business. Product variety has risen dramatically. Supply chains have extended around the world driven by low-cost sourcing. Product complexity has risen. Outsourcing is more prevalent. Product life and development cycles have been reduced.
This has served to create a huge gap between customer expectations and the reality of what it takes to fulfill those expectations reliably. This will not get better anytime soon. The proliferation of quicker delivery methods such as drones will simply serve to widen this disparity between customer tolerance time and the procurement, manufacturing, and distribution cycle times.
Add to this an increased amount of regulatory requirements for consumer safety and environmental protection, and there are simply more complex planning and supply scenarios than ever before. The complexity comes from multiple directions: ownership, the market, engineering and sales, and the supply base. Ultimately, this complexity manifests itself with a high degree of variability and volatility. This variability is making it much more difficult to generate realistic plans and maintain the expectation that things will go according to plan.
But are conventional planning systems just not implemented correctly, or are they having difficulty keeping up with these circumstances, or are they, in fact, making it worse? Could these systems actually be exacerbating the inherent increased levels of variability in this “new normal”? Could they be producing plans that are both exceedingly unrealistic to start with and exceedingly susceptible to the increased level of variability at the execution level, causing the organization to expend massive amounts of resources to compensate operationally as well as limiting the potential for improvement through methods like Six Sigma, Lean, and Theory of Constraints?
In order to answer these questions, we will need to expose another key component of our flow equation—the component that eludes most companies in today’s complex and volatile supply chain environments.
There is an important factor in managing variability that must be recognized; without it the quest to reduce or manage variability at the systemic level is a quixotic one at best. This missing element is labeled “Visibility” in Figure 1-12.
FIGURE 1-12 Adding visibility to the equation
Visibility is defined simply as relevant information for decision making.11 A company cannot just indiscriminately move data and materials quickly through a system and expect to be successful. Today organizations are frequently drowning in oceans of data with little relevant information and large stocks of irrelevant materials (too much of the wrong stuff) and not enough relevant materials (too little of the right stuff). When this occurs, there is a direct and adverse effect to return on investment. Sophisticated analytics of bigger and bigger databases does not solve the problem but rather deepens the ocean of data.
Finding a Core Problem
Thus the flow of information and materials must be relevant to the required output or market expectation of the system. To be relevant, both the information and materials must synchronize the assets of a business to what the market really wants; no more, no less. Having the right information is a prerequisite to having the right materials at the right time. With this is mind, Plossl’s law can be amended to:
All benefits will be directly related to the speed of flow of relevant information and materials.
Note that this formula starts not at flow but at what makes information relevant. If we don’t fundamentally grasp how to generate and use relevant information, then we cannot operate to flow. Moreover, if we are actively blocked from generating or using relevant information, then even if people understood there was a problem, they would be powerless to do anything about it. Thus, we have reached the core problem plaguing most manufacturers today; the inability to generate and use relevant information to drive ROI. Without addressing this core problem, there can be no systemic solution for flow.12 Figure 1-13 shows the core problem area of the equation versus the area associated with Plossl’s law.
FIGURE 1-13 Core problem area of the equation (from Smith and Smith13)
Intuitively, people in organizations know that they must find and use relevant information for decision making. Yet many of those people recognize that their systems are not giving them the visibility that they need. Another question from the 2014 poll of over 1,000 Certified Management Accountants across 41 countries conducted by the Institute of Management Accountants clearly shows a problem. The question was:
How would you rate your ERP system’s ability to focus on the relevant information?
| a. Poor | 22.5% |
| b. Moderate | 60.8% |
| c. Good | 16.7% |
Well over 80% rated their systems’ ability to provide relevant information either poor or moderate.
A Deeper Understanding of the Bullwhip Effect
With this expansion and segmentation of the equation, we can see the bullwhip effect in a slightly different light. The bullwhip effect is the manifestation of the core problem area in Figure 1-13. Figure 1-14 provides an amended view of the bullwhip effect.
FIGURE 1-14 Restatement of the bullwhip effect
As you can see in Figure 1-14, distortions to relevant information go up the chain, growing in size and causing wider and wider oscillations in terms of both quantity and timing requirements. Distortions to relevant materials come down the chain as delays and shortages accumulate. These distortions directly contribute to the bimodal inventory distribution and its related effects are seen at the organizational level, the need for users to employ alternative methods to make sense of it, and, finally, why return on investment performance is lagging.
