What FMCG can learn from tech giant’s strategy for driverless cars
From identifying the source of cholera outbreaks in 19th century London to cracking enemy military codes in World War II data has for centuries been used to solve some of the world’s biggest challenges.
These days the data-driven opportunities for businesses are incredible. In fact we have yet to come across a business challenge that data cannot help to solve, if you know what to ask.
Some Quantium leaders were recently fortunate enough to tour some driverless car facilities in the USA. What they learned was that successfully commercialising the driverless car depends on being able to answer four seemingly simple questions:
• Where am I, precisely?
• What is going on around me?
• What will happen next?
• What should I do now?
Driverless cars can only really work at scale when the vehicles can safely answer these questions accurately, consistently and at speed.
The challenge for most organisations today is largely the same, and the ability to answer those same questions more effectively than your rivals will provide an enormous competitive advantage.
Easier said than done.
In todays’ businesses, execs are making hundreds of decisions every day, based on thousands of factors and pieces of information. The truth is that pace and complexity has far outstripped human processing and decision-making capacity.
This is where data science and AI can play a crucial role.
In FMCG, there are opportunities right across the value chain. Here are three key areas where we see the most immediate value:
Forecasting – Forecast optimisation delivers benefits across the supply chain including manufacturing, production, inventory, shipping and waste, and ultimately provide a superior customer experience. AI can be transformational when it comes to predicting demand across thousands of products in hundreds of locations with a myriad of potential drivers, achieving a level of granularity and accuracy that hasn’t previously been possible. (Read more about AI based forecasting here.)
Trade spend – Arguably the most important focal point of the supplier-retailer relationship, and a significant financial investment, deciding “what should I do now?” with regard to trade spend is notoriously difficult. An average category of 10 SKUs, each with 6 possible price points over 26 weeks, for example, has more possible calendar combinations than there are stars in the Milky Way. Not surprising therefore that the manual optimisation of trade spend is a virtually impossible task. AI, on the other hand, can process this data at unimaginable speeds with 100% accuracy.
Personalised communication – When it comes to brand interactions, people want it all. Quality and value, choice and convenience, whenever, wherever and however they want it. Everything tailored just for them. Technology has enabled it, and brands like Amazon and Netflix have conditioned consumers to expect it. Advertising the right product in the right way to the right people at the right time requires significant data and computational power, but is now eminently possible.
At Quantium, we’ve seen five-fold improvements in clients’ results from machine learning approaches in personalised communication and double-digit improvements in forecasting accuracy through tailoring decision engines to the needs of our clients.
If you are still tackling your business’ biggest challenges the same way you were even five years ago, you are potentially leaving a massive amount of value on the table. It’s like trying to solve problems with an abacus whilst your competitors are using a supercomputer.
No doubt a time will come when the driverless car can answer those four not-so-simple but crucial questions, and in doing so will transform not just an industry, but the entire transport system.
If you’re ready to explore the potential for data science and AI to transform your value chain, and unlock the power of getting those answers right for your business, we’d be delighted to speak with you.
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