"Without data, you're just another person with an opinion." - W. Edwards Deming.
In today's fast-paced business environment, making decisions without data is like navigating a ship without a compass. As W. Edwards Deming famously said, "Without data, you're just another person with an opinion." This quote perfectly encapsulates the importance of data-driven decision-making in modern business practices. Yet, having data isn't enough—it's what you do with it that truly matters.
The first step in a data-driven decision-making process is collecting and analyzing it. The next step is transforming it into actionable information from which you can gain insights, with the ultimate goal of taking the best possible actions.
This transformation is crucial, especially when implementing a new planning system to cope with today's complex global supply chains. Supply chains are no longer linear "chains" but intricate, interconnected networks, so getting this transformation right can create a significant competitive advantage.
So, before embarking on a massive planning 'data collection and transformation' project, I encourage all executives to ask one critical question at the start of that process: “Is this new, accurate, updated, and enriched information relevant to the actionable decisions you expect your team to make?”
In the world of Demand-Driven MRP (DDMRP) planning, this question has been asked about the most famous and sought-after piece of information—the forecast. DDMRP questions the relevance of using the forecast as the primary demand signal in the operational zone. The operational zone is the period when any changes or decisions are constrained by the lead time. So, instead of driving operational planning decisions with the forecast, in DDMRP, we believe the actual customer orders are more relevant and thus build our processes around fulfilling the real demand rather than satisfying a forecast, which is not real demand. Thank you, LEAN!
At B2Wise, we've seen firsthand how our approach has transformed hundreds of businesses, leading to higher service levels, lower inventory, fewer expedites, more stability in the operational zone and overall less chaos. That said, this doesn't mean we don't need a forecast in our end-to-end supply chain planning process! It is still highly relevant for strategic planning, where we use S&OP (Sales & Operations Planning) to maximize capacity utilization or determine the need for additional capacity. The same applies to tactical planning, where we use processes like RCCP (Rough-Cut Capacity Planning) to ensure we have enough resources in place well before placing orders. In these planning horizons, the forecast is highly relevant.
In line with this, at B2Wise, our innovation team has been working on a new approach to forecasting, which we call Stability-Based Forecasting. It leverages leading industry processes such as data cleansing, hierarchical forecasting, and AI algorithms to transform data. However, the critical difference is that when a user adjusts a forecast within the operational zone, we test the relevance of this adjustment by checking if the buffer can absorb it, ensuring no unnecessary changes are made, thus protecting the stability of the plan. If there is a need to apply a change in the demand signal, we create an 'Event Order' that forces the user to be very specific about this demand signal change. We then treat this as a Spike Order, allowing you to control exactly how this additional demand is prioritized and managed rather than it being lost in a single forecast number.
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In conclusion, the value of data-driven decisions cannot be overstated. But remember, it's not just about having data—it's about turning it into meaningful information that drives stable, efficient, and effective planning decisions. Always ask yourself if this new AI-enhanced information is relevant to the decision I am about to make.
Lead Data Scientist at EREA consulting| Passionate About Using Data to Solve Real-World Problems | Always Open to Learning and Collaboration
1 个月DDMRP is great?
Well done!