This post was written by Dr. Gerhard Plenert, author of Supply Chain Optimization through Segmentation and Analytics.
We tend to get ourselves locked into a one-size-fits-all solution mentality. We solve a problem and because a particular solution worked for us we automatically replicate that solution by attempting to apply it to every problem we encounter. We talk a lot about “out of the box” thinking, but we feel more secure by staying inside our solution box.
The one-size-fits-all dilemma also applies to solving Supply Chain problems. For example, if a particular planning solution works effectively for one product line or customer or supplier, then it must also be the best solution for all product lines. And we apply this solution across the board. Then we stand back and wonder why it didn’t work when we knew for sure that it had worked well in the past.
There have been one or two tell-tale signs that Santa and his expansive operation of Elves and Reindeer have been struggling to cope with their commitments in recent years.
Picture this: you are in charge of demand planning at a firm supplying essential base material to various markets, involving OEMs and CP companies. Your challenge is to balance the carefully established forecast with client demand. Since clients usually don’t adhere to the forecast, your task is to address the gap that emerges between your plan and actual demand, and assign the ‘pain’ to either sales or supply. Armed with ‘rules of thumb’ (product demand with high margin prevails over lower margin) and ‘guidelines’ (segment A clients have priority) you pass your judgment. Day after day, you experience that reality requires many more trade-offs than your guidelines allow for. How often are your verdicts met with approval?
My Twenty years of Supply Chain Operations, Consulting and Business Management drew to a close in the Spring of 2014 as I elected to take a break from my career and invest 100% of my time into family. It’s been a fairly wild journey which consisted of operational roles in warehousing and logistics across Europe followed by a consulting and business management career that had me employed by companies headquartered in London, Paris, Virginia and Bangalore.
Recently, we covered four great examples of how organizations are using optimization technology to address social problems in innovative ways. In a similar way, this post highlights four ways optimization can be leveraged to add value to your company’s supply chain.
“Innovation differs from invention in that innovation refers to the use of a novel idea or method, whereas invention refers more directly to the creation of the idea or method itself. Innovation differs from improvement in that innovation refers to the notion of doing something different rather than doing the same thing better.” – Wikipedia on “Innovation”
This year’s Gartner summit gravitated strongly towards innovation. In terms of their DDVN (Demand Driven Value Network) maturity model, they focused on the deployment of relatively new ideas or methods on Stage 4. In their language, the focus was on progressing from an ‘Integrated’ supply chain to a ‘Collaborative’ supply chain. Steps in the process fall into two categories: those that work on enabling collaboration, and those that seek to get value out of collaboration.
Interesting as they are, the finding that intrigued me the most at the conference was the struggle to find the right supportive technology. With each conversation we had, be it with companies or analysts, the point was being made that progress had been delayed by the struggle to find the right technology.
Long-haul oil transportation is a multi-million dollar operation for large oil companies such as Petrobras. The difference between a reasonable and a good transportation schedule may involve millions of dollars in cost savings. To properly schedule each shipment, planners must find a match between cargos, vessels and destinations. Petrobras is one of the players in the spot market of chartering and renting out long-haul oil transportation vessels. How do they manage to combine the computational aspect of searching through the vast space of possible schedules and the human aspect of operating on the spot market of chartering and renting out vessels? This blog post offers an insider’s look into the AIMMS-based decision support system (DSS) that is currently being used by Petrobras to tackle this ship scheduling challenge. Continue reading »
Since we started this blog, we’ve been exploring how supply chain optimization can aid the decision-making process and bring organizations better results. We have covered a multitude of methods and techniques applied in the pursuit of supply chain excellence, and have discussed some of the most pressing challenges faced by today’s business leaders. Today, inspired by our mission to bring the benefits of optimization to society as a whole, we will look at 4 inspiring AIMMS use cases which leverage optimization technology not only for business advancement, but for the greater good. Continue reading »
Key trends in SC continued, as seen at the 2014 European Supply Chain & Logistics Summit in Barcelona
It was great to visit the European Supply Chain and Logistics Summit again this year. On the whole, supply chain leaders seem to be recovering from the blow of the economic downturn, and are looking ahead to seize opportunities. This contrasted with last year’s SC&L Summit, which was all about declining demand in the face of global economic change. The prospects then seemed daunting. But there were also some positive things. For instance, companies started realizing how important it is to leverage SC Analytics, and there was the growing notion that investing in excellent SC people actually does make a difference. Continue reading »
This is a guest entry by Luciano de Moura, Managing Partner of UNISOMA – Analytical Planning Systems (an AIMMS implementation partner). Luciano has a Master’s Degree in Automation and Intelligent Systems from UNICAMP. The article below was originally published in the Brazilian magazine Mundo Logística.
There is no doubt that the first step towards good quality planning of the supply chain is to make decisions using common sense. But what if these decisions depend on hundreds or even thousands of variables and constraints? And what about cases where the process is so complex that potentially interesting alternatives remain unexplored? And what does this mean for the situations where the scale of production makes it such that even small changes to the plans translate into millions of dollars? This article demonstrates that relying less on common sense and instead basing planning decisions on the efficient use of analytical tools is the safest option to ensure the best results for the company.
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