| | 9 DECEMBER 2021software. In other words, you need to mobilize your teams on new problems, before starting to solve the problems you had before. Instead of working on optimizing your Supply Chain, they optimize the model, the software.· Costs : For implementing an APS you need to spend money on the the licences and support / maintenance for the software, on the consultants helping you to overcome the complexity of the project, on the IS/IT integration, on training. Don't forget 3 other things : opportunity costs (what you could have done with the same money, on BI solutions for instance), the time and efforts to actually get the funding from your CFO and general management and the time you spend proving that you actually do better with the new tool.· Yes, extreme difficulties to prove that you are actually better off with the systems than without it, especially if you consider that you could have spent all this money differently.· Fixed solution : APS vendors will tell you their solution is super flexible and can perfectly describe your Supply Chain and help you optimize it. From my experience, all Supply Chains are unique. What makes your company's offer unique is also what makes it's Supply Chain unique. Integration of the value chain, diversity of suppliers, markets, customers, constraints, opportunities, make a complex system which is absolutely unique.· Data : Most APS are quite rigid in the way they require data. Don't forget that your Supply Chain is visible only throughy our data. How many errors and approximations are you going to make trying to fit your data into the data model required by the APS ? Only part of the data you provide is exactly what the APS needs. As a result, the model of your SC (digital twin as it's called now) can be Incomplete and fairly wrong.· Flexibility : Once you get your APS implemented, don't you think you'll need to update it? Tweak it? Adjust it? How do you run continuous improvement through a fixed IT solution? Yes, exactly, you use BI solutions on top of it, because you are probably sick and tired already to go through the change request process to close the gap between the tool you have and the tool you need.2. Where should your BI team sit ?The first question is already: do you need an BI team at all? Or do you need BI trained Supply Chain experts? I have seen both work. The critical success factor is that these people know your Supply Chain. And as I explained it earlier, a large part of your supply chain is actually the data coming out of your ERP, ordering systems, WMS, TMS, APS. It means that the experts need to perfectly know how and when each piece of data is generated. What does this data mean? This quantity? An IT expertise is definitely needed in building the back-end of the data cube. Data must be made quickly available in a semi-structured form allowing fast queries. At the time you build this cube, you don't know which queries will be developped later on... because optimization needs will come only later on. There is actually no limit as you don't know which ideas you'll have in 6 months, which request you'll get in 12 months from top management to improve your procurement, production or sales. That's the whole point. There is only a short list of predefined queries that you can run everyday for the next 3 years. Most queries get outdated super fast as your business changes. I'm sure Consultants can come up with 5 maturity stages on BI solutions and teams set up (and you'll probably sit between maturity stages 1 and 2 so that they call bill you hours to help your each the next stages !). I'm also sure you'll need to fight with IT to keep BI competencies in your SC teams, or in direct control of your team.And by the way, how do BI solutions compare to APS? In my view, they do better on all aspects : costs, speed of implementation, adaptation to the uniqueness of your SC, focus on actuall issues and opportunities vs creating new issues, and most importantly they support continuous improvement, as long as they are run in an agile way.3. How does Data Science change the picture ?My view is that progress Data Science makes APS even less relevant.Data Science brings two benefits to SC professionnals on top of the current BI strengths. a. Possibility to manipulate even larger unstructured data setsb. Sophisticated statistics. I will develop this benefit, that most APS actually don't bring. Mastering a Supply Chain consist in reducing, anticipating and absorbing variability. The way we have done it for the last 25 years has been quite empirical. I will not develop further the limits of those approaches (one is for instance the used and abused assumptions that most variability is normally distributed, which, we all know, is quite wrong) but will insist on how modern data science actually fits to SC needs in the sense that Data Science tools are mastering analysis of variability. Mastering a Supply Chain consist in reducing, anticipating and absorbing variability. The way we have done it for the last 25 years has been quite empirical
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