3 tips for setting up supply chain AI

Published: 05 / 02 / 2019

With today’s businesses generating more transactions and creating more data every minute, data optimisation is key to managing your global supply chain.

Faced with so much data, traditional supply chain management processes have struggled to keep pace. Pinpointing a problem with legacy systems can feel like a Herculean task. However, artificial intelligence (AI) may hold the solution.

AI has become a big topic of conversation in supply chain management circles, with many businesses already taking the plunge. By applying AI and machine learning to huge sets of data, these companies are uncovering performance insights and meeting challenges that were previously out of reach.

According to Gartner, 25% of organisations embarked upon AI initiatives in 2017. In 2015, this figure was just 10%. AI has the potential to completely transform supply chain processes across a range of industries.

If you’re looking to introduce AI into your business supply chain, these three steps will help to get you started:

1) Focus on a specific problem

For those starting out in AI, it’s best to identify and target one particular issue in your supply chain. This will help focus your efforts and make sure you get the best results. Choose an issue that’s negatively impacting your efficiency, customer experience or profit margins.

It may seem impossible to pick just one target issue, but by doing so, you’re reducing the likelihood of project stagnation or abandonment. You’ll be able to take what you’ve learnt from an initial bespoke project and apply it to other, future AI-driven initiatives.

2) Be AI-ready

AI readiness depends on the depth of your data. In an ideal world, AI is applied to data sets of deep granularity. For example, this could be three years of data with daily transactional-level granularity. However, in reality, data is often drawn from a range of systems and data sets with inconsistent time frames. This can present difficulties for AI systems.

By preparing your data collection and storage mechanisms for highly granular data, you’re preparing for AI. AI readiness doesn’t mean you need a data science team, but you do need people with the right skills and expertise to guide you through the AI environment.

3) Consider a partner

As is often the way with emerging technology, the success of supply chain AI largely depends on your choice of partner. Take the time to find a partner who can meet your needs and won’t limit your development. And remember, any partnership should be a two-way street. Ideally, you want to leave your C-suite open to innovation. And be prepared to have your assumptions blown out the water.

Supply chain AI can feel like a step into the unknown, but it has the potential to totally transform supply chain management. At Adare International, we’re as serious about supply chains as we are about emerging technologies. Find out how we can help your business – contact the team today: hello@adareinternational.com.

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