HOW ACCURATE AI-DRIVEN FORECASTING CAN AUTOMATE DEMAND PLANNING AND OPTIMISE SUPPLY CHAINS


To improve your demand planning, modernise your demand forecasts and supply chain IT. A female supply chain specialist optimising her inventory

Organisations in different industries seem to be aiming for supply chain optimisation, which is clearly an understandable goal. With Covid19 and consequential supply chain disruptions as well as other external factors, supply chain planning has turned out to be merely an impossible task for some. As a result, business leaders are looking for more advanced technologies, especially in terms of demand planning.


To put it simply, it’s all about the demand forecast. It’s a bottom-up approach where demand is forecasted to better plan resource deployment in accordance with the forecast. That means, for instance, procurement of products and/or raw materials, i.e. how much and when; it means inventory management, i.e. not having too much cash tied up in inventory, and not having too little and risk stockouts; it means production planning, where production is scheduled according to expected deliveries etc.


Obviously, all those operational challenges depend on the demand forecast. Or, more importantly, the demand forecast accuracy. And it’s the lack of accuracy that stands in the way of automated demand planning.


According to a recent McKinsey survey, 73% of respondents claim their supply-chain functions rely on spreadsheets. Although it’s a surprisingly high number considering the technology available, the reasons are usually quite simple. The supply chain management software out there deliver very unreliable demand forecasts, which always puts the demand planners in a position where they have to look into the numbers themselves in spreadsheets, where the most common approach is to look at the sales at the same time last year and/or the sales development for the past months. It’s called guesstimating, and it is one of the largest factors behind supply chain inefficiencies as it lacks accuracy.


And that’s precisely what’s being underlined here; businesses can’t automate demand planning if your demand forecasts lack accuracy.


“Supply chain optimisation depends on accuracy and automation”


It is easy to argue that supply chain optimisation depends on accuracy and automation, but it certainly goes hand in hand - you can’t automate without accuracy. And AI-powered technology is opening up the possibility for organisations to get there.


Demand planning is a tough task, as demand is rarely constant and external factors (out of our control) have major impact on the supply chain effectiveness. When organisations adopt automated forecasting models powered by machine learning, the systems can rapidly evaluate millions of data points, both internal as well as external variables, to uncover the drivers of shifts in demand, a critical aspect when automating the process.


For instance, a European manufacturer ran out of certain raw materials in one of its plants and faced a decision of complete production line shut-down, or to manufacture other products instead, and then, which products? Accurate demand forecasts helped planners schedule production of other products and made them prepared when demand more than doubled in a number of categories. As this happened during severe Covid lockdowns at a time of major uncertainties, planners had been operating in the dark if it wasn’t for superior AI-powered forecasting technologies that took into account governmental-forced Covid measures, supply chain disruptions, and shifts in demand.


The best way to explain the importance of accuracy is to imagine the extremes. If one could forecast with 100% accuracy (which is obviously not possible) then all supply chain planning could be 100% accurate; i.e. exactly the right quantity procured at exactly the right time; inventory optimised; production schedules optimised; distribution of exactly the right quantity at exactly the right time, and zero waste. But as 100% accuracy cannot be achieved, it still tells us that more accuracy will reduce waste, and the higher the accuracy the more saving.


New AI-driven methods in forecasting are simply changing the game and opening up tremendous possibilities for automation within demand planning.



 


Sumo Analytics pioneers innovations and developments in advanced forecasting technologies based on AI, and delivers unprecedented levels of accuracy. It may feel daunting, but modernising the demand planning systems is easy with the right approach. The potential benefits are significant: superior and automated planning processes, systems that are tailored to the organisation’s needs, and ultimately, a more efficient and resilient demand planning process.



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