COVID, hybrid working, Brexit and war in Ukraine have made forecasting of volume, product mix and pricing difficult across sales, supply chains and distribution channels when using historical data and simple methods.
Inability to forecast can mean last minute supply cost increases and missed chances of value based pricing affecting profitability.
In times of greater volatility, changing factors of demand and uncertainty, AI can perform much better than traditional forecasting methods1 by removing noise and using methods such as systemic, environmental, and dynamic observable factors to provide insights your company can utilise when patterns are not very obvious in marketing areas including consumer behaviour, product or channel usage.
With better AI enabled demand and supply forecasting, companies can use powerful AI pricing algorithms that incorporate laws of economics, management control systems, psychographics, consumer behaviour and heuristics pricing strategies. They can be applied dynamically (e.g. daily, hourly, and real-time discounts) or periodically at much greater speed and accuracy than traditional methods. These AI pricing algorithms are already in use by larger companies when shopping online.
Companies can benefit more by combining AI pricing with quality based lean distribution channel optimisation that better match channel capacity and costs to forecast demand, improving agility, cash flow and profitability.
Like to explore a quick, test or pilot without much investment? This explainer is part of our AI in marketing series covering different applications of AI marketing. Please see other explainers by visiting our how does it work page or if you would like to have a quick chat with our marketing or AI experts, connect with us.
References
| ↑1 | Can AI deliver tangible benefits to demand forecasting? IMD Research and Knowledge |
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