Market sensing with AI: Turning external factors into strategic opportunities
AI can empower business leaders to shift from reactive response to proactive market sensing, using real-time data to enhance forecasting accuracy, optimise inventory and manage financial risks like the bullwhip effect.
The conversation around artificial intelligence (AI) and its role in supply chains is gaining momentum. A common discussion point we hear is how AI can be leveraged to “bring the outside in” when it comes to tactical planning. Specifically, how can it be used to continuously monitor and analyse external factors such as market conditions, consumer behaviour and competitor activity in order to improve demand forecasting, inventory management and overall decision-making?
In essence, it’s about moving from reactive tactical planning – where we respond quickly to market changes after they’ve occurred – to proactive market sensing, where AI allows us to detect early signals and respond to potential disruptions before they fully materialise, positioning the business to not only minimise impact but also capitalise on new opportunities.
While the ability to predict external events before they unfold is an obvious advantage for Supply Chain teams, this value might not resonate with the rest of the business until it’s discussed in financial terms. Let’s take a look at how to do that.
Discussing market sensing in Finance-friendly terms
As Finance and Supply Chain departments work toward better collaboration through an integrated business planning (IBP) framework – and as Supply Chain leaders become increasingly fluent in critical financial metrics like EBITDA – it’s essential for operational leaders to prove the value of market sensing while making the case for AI investment.
Naturally, your business case should be as specific as possible around the anticipated ROI relative to the investment, whether tangible ROI (likely to provide more immediate value) or strategic ROI (an investment in capabilities that serve a strategic or long-term purpose).
One path to explore is how AI-driven market sensing can help manage the bullwhip effect in your organisation, where minor demand fluctuations snowball into major inventory imbalances as they ripple through the supply chain – leading to excess inventory, stockouts, higher costs and ultimately lost sales.
That’s bad news for any business, but to make a strong case for AI investment, it helps to quantify the financial impact: when too much cash is tied up in inventory, liquidity suffers, and when stockouts occur, cash flow takes a hit.
In both cases, the cash conversion cycle is negatively impacted, leading to financial stress – which market sensing can help mitigate.
Brewing innovation with market sensing
A great example of market sensing through AI comes from a multinational coffee roaster and retailer, using technology from one of our partners, o9.
With significant investment in data science, the company can accurately forecast demand for coffee and hot beverages at a store-SKU level. This includes factoring in leading indicators like weather patterns and local events. To capture local knowledge, they developed an app that allows baristas to input relevant market details – such as an upcoming football game or a university graduation nearby. Changes in weather or local activities automatically trigger replenishment actions based on o9’s “digital brain”.
Critically, the company has proven the value of this approach in both quantitative terms – such as time saved on manual planning and reduced food waste – and qualitative benefits, including enhanced assortment planning and quicker adaptation to demand shifts.
AI: three key takeaways
There are three key points to round out this conversation. First, while the overall perception of AI’s potential has improved recently, the fundamental message remains: don’t get swept up in the hype. AI, like any new technology, can be the right tool for certain jobs in your organisation; however it won’t be suitable for every scenario.
Secondly, no matter how you implement AI for operational support, the conversation should begin strategically. Always ask yourself this: “What value do we aim to deliver, and how will we measure it?” Also, consider the impact on people, processes, and systems early on. AI is an enabler, not a solution to be used in isolation, and it needs to be carefully integrated into existing structures.
The third and final key message is definitive: the time to act is now – waiting around to see how AI plays out is no longer an option. It might still feel like a slow-burn, but it’s only a matter of time before the flames are fanned and you risk a burning platform crisis moment.
If you’re not already exploring AI’s potential, you risk falling behind, and catching up will be an expensive game of investment down the road.
We are enablers of change and transformation in Supply Chain, Financial Planning & Analytics, Information Management, Management Consulting, Project Management, and Managed Application Services. Contact us to find out more about how we work with your teams or call 1300 841 048.
