Category archives: analytics
The Brexit is a reality and with it, companies in Europe are facing even more uncertainty than before. There is serious concern that the UK’s decision to leave the EU will bring further destabilization and economic risks. How will it impact your supply chain and your bottom line? This article discusses 5 key things supply chain leaders should consider post-Brexit. It also explains how analytics can help you determine the best way forward. Specifically, I will explore how Prescriptive Analytics can help you improve decision-making and make data actionable in an increasingly volatile economic landscape, instead of only providing insight into your data’s behavior.
Precise means being exact, accurate and careful about details. The difference between good and great. As we discussed in our recent Supply Chain webinar, this is not an easy task if you have a lot of fluctuating demand and uncertainty in your production process. During the webinar, Paul Coombe (Supply Chain Director at Nampak Glass) shared his insights on making the best possible use of your production facilities and optimizing the way you respond to changes in demand. This is particularly difficult at Nampak, a business that aims to produce 350 tons of glass per day while managing different production processes for different bottle types and maintaining customer service at a profitable level. The interview below summarizes how Nampak tackled this challenge.
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?
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 »
Back in 2008, companies tried to release cash from inventory reductions to respond to the first recession’s wave. But this had some unintended consequences. Roughly 80% of them ended up with more inventory levels. Why? Because they adopted a quick fix, an opportunistic approach which forced them into silo planning and severe departmental disconnection. How could they have avoided this? When you look back, the answer is simple: Integrated Business Planning (IBP) and Optimization. My colleague Marcel has written about IBP and Optimization before, and walked you through some of its real business gains. In this post, I will attempt to explain why demand modeling and planning is an imperative in the IBP cycle and what the symbiosis between sales and marketing looks like within the cycle. Continue reading »
This time I feel like writing about something that I’ve encountered in my work since I joined AIMMS over a year ago. It probably will be a shorter blog post than you’re used to, but hopefully equally inspiring.
In speaking with our business relations, I often find myself wondering how to best explain what optimization is all about. For math people, it’s easy. They will refer to a set of variables (i.e. the subjects you need to decide on) that you assign values to in such a way that the objective function (your goal) is maximized (or minimized) within the boundaries of a set of constraints (restrictions). This is formally true and it’s important to grasp the concept so you can easily go back to the basics.