A recent post over on Spend Matters UK from Andrew Nichols boldly states that Artificial Intelligence Can Help Procurement Solve Some of the Big Challenges. In fact, he predicts that AI in the not so distant future will play a major role in the international supply chain, supporting businesses to solve a number of very contemporary problems.
In particular, Andrew believes that AI could identify new markets, manage supply chain risks, track exchange rate volatility, and find the best value without compromise on quality.
If this were true, Procurement would not be needed at all, and the C-Suite would be chanting “Procurement is Dead. Long Live the Machine! Our Samaritan has Arrived!” If an AI (which does NOT exist by the way, intelligence is not artificial) could do that, you’d all be fired, because, let’s face it, when it comes to managing supply chain risks, tracking exchange rates, identifying new markets, and always finding the best value, your batting average is less than that of a major league baseball pro.
An AI can give you market statistics, and break it down by region, demographic, competitor, and product. It can NOT tell you how appropriate a market is for you. You have no idea why a market is good for a competitor. You can cross-correlate it’s products to other top selling products on the market and identify common features, common advertising channels, and common comments across brand surveys, but the best you can draw is conclusion based on correlations. Correlation is not causation. You could take the highest ranked strategy suggestion from the analytics engine, implement it, and flop miserably because a key factor was missed, flawing the entire model.
An AI can compute, for every product in the world, the cost to value ranking using market costs, exchange rates, correlation to desired feature lists, and consumer ratings, but this is not the best value. The best value is that where the cost to value formula is based on your value rankings, which could be much more heavily dependent on reliability, safety, and service than look, feel, and flash. And since your organization will not have every product rated, the best the AI can do is suggest the most likely candidates for human review.
An AI can detect the presence of risk indicators that you have defined against known risks, it cannot identify risk indicators for unknown risks. If the algorithm doesn’t understand that a tsunami is a risk because it can damage harbours and destroy coastal plants, the risk will not be identified until it discovers a news story about how the supplier plant had to shut down. And if it does not understand that legal proceedings can bankrupt a small company, it could overlook a filing with the potential to bankrupt the supplier. If the supplier was strategic, that is something the organization would want to know about immediately.
An AI can track exchange rate and give you a real-time view into which is the most preferable rate, the short-term and likely long-term trends, and give you suggestions with an expected level of confidence within plus/minus x%, but can not necessarily predict the right currency to use to lock in a long term value for any better than a human expert. No known algorithm knows all the factors that contribute to exchange rates, how to detect their presence, and how to incorporate them. There are a lot of advanced statistical algorithms that can model the trend curves well, but they assume that markets will more or less keep the status quo, which never happens. Their projections are useful, as they can identify which currencies are likely to be best and where inflection points are likely to occur, making the best use of an experts time, but they cannot replace the expert.
And if any CPO were to try and replace a team with an AI for one or more of these functions, then he would quickly bring an end to Procurement in his organization because, while it would succeed in many cases, sooner or later there would be a spectacular failure that would cancel out all of the previously identified value, putting the entire organization at risk.