Matching supply to consumer demand is tricky at the best of times, even without the vagaries of a global pandemic to contend with. While an efficient demand forecasting strategy can drastically improve the accuracy of forward planning, there’s always an unavoidable element of subjectivity that’s hard to overcome. Machine Learning (ML), however, is improving the accuracy of demand forecasting even more, so that businesses can be more responsive to changeable markets.
How Machine Learning Is Changing The Face of Demand Forecasting
When used as part of an advanced demand forecasting platform, such as Reflex Planning, machine learning increases the range and depth of data points available to demand planners when making sales predictions – leading to more accurate and responsive sales forecasts. Rather than depending on a single data source, such as past demand, to make forecasts, a modern software platform will analyse the most relevant trends from multiple sources, including:
- Sales reports and historical financial data
- Marketing polls
- Social media indicators, such as surges in followers, shares, and retweets)
- Weather forecasts
- Customer POS information
- Website reviews
- Marketing campaigns
Machine Learning constantly applies complex algorithms to real time data changes so that demand signals are spotted, patterns are recognised, and complicated relationships are uncovered in large amounts of data (relationships that are easy to miss when plotting demand trends manually). As well as being able to analyse volumes of data far larger or more complex than a human could unaided, ML also – critically – adapts to changing market conditions, even when these happen quickly or with little warning.
Demand Forecasting Models With Machine Learning
Because of its flexibility, ML can be used to produce different demand forecasting models, including new strategies such as:
Predictive Sales Analytics
When combined with statistical methods, ML can deliver more than just estimates of consumer demand, but an understanding of the drivers of sales and predictions of consumer behaviour in different situations.
Machine Learning can spot real-time variations in consumer purchasing behaviour, so that businesses can respond promptly to volatile markets. By extracting data from POS systems, warehouses, and external sources of information, ML can determine the importance of each variation in purchasing behaviour, analyse factors, and deliver adjustments to accommodate market volatility.
Ready To Improve The Accuracy of Your Demand Forecasting?
If you’re seeking trustworthy and reliable ways to improve the quality and accuracy of your demand forecasting, get in touch with Reflex Planning for a free demonstration of our industry leading forecasting software. Our end-to-end S&OP software harnesses the latest technology so that you can accurately forecast demand by day, week, or month, and organise and plan your resources for future scenarios.
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