Predictive Sourcing: How to Act on Market Changes Before They Happen

The past year has repeatedly proven that the best-laid plans can fall to pieces with little or no warning. Among the many issues we’ve all had to deal with have been shortages. And it’s not just consumers who have experienced the frustration of scarcities, although we all have memories of lining up for toilet paper and disinfectant wipes. Knowing how to act on market changes before they happen is difficult for all, from individuals to large organizations. Many companies have been sideswiped by shortages through their supply chain, leaving them unable to keep up to demand—and in some cases idling production lines—because components and materials aren’t available.

The past year has provided many examples of the fragility of the global supply chain and the dire results of being caught off guard by a shortage or a run on demand. First, everyone heard about rampant grocery shortages, then construction. Now, the latest victim has been the automobile industry.

A Global Microprocessor Shortage Paralyzes Automakers

Demand for new cars is sky-high. Dealerships are welcoming buyers after being closed on and off for the past year. Many people who had been working from home are returning to commuting and wary of public transit. Road trips are a big thing as summer vacation season kicks off.

There’s a lot of pent-up demand for new cars, and interest rates are still near record lows, making car loans affordable. Automakers should be churning out new cars and trucks and capitalizing on the surge in demand. Instead, many assembly plants have halted production, and a shortage of new vehicles is pushing buyers to choose used automobiles. What happened?

Automakers were caught off guard by a global shortage of microprocessors.

Demand has been ramping up for consumer electronics like smartphones, laptops, TVs, and new game consoles. They all use microprocessors, which caused a spike in global demand for the chips. At the same time, Chinese companies were stockpiling microprocessors as protection against the ongoing U.S. trade war.

Then a key Japanese chip production plant suffered a fire, worsening the situation. The global microprocessor supply chain was hit with a double whammy. It was working hard to meet a demand that had suddenly surged; at the same time, that production capacity was unexpectedly reduced.

The increasing sophistication of automobiles means they are packed with microprocessors. There’s an average of 1,400 chips in a typical vehicle. With the supply of chips disrupted, some automakers have been forced to shut down their assembly lines. They are losing customers. At this point, it’s projected the semiconductor will cost automakers $110 billion globally in 2021.

Nothing could have prevented the chain of events from resulting in a global microprocessor shortage. And with new chip fabrication plants costing billions of dollars (not to mention the many months needed to construct them), there is no easy solution.

However, some companies have felt the pain less than others. Why? Because instead of reacting to the shortage after the fact, and scrambling for chips, their procurement function used predictive sourcing which allowed them to predict market changes, and act on market changes before they happened.

What Is Predictive Sourcing?

Predictive sourcing is a new, first of its kind, groundbreaking development in the world of procurement.

All procurement teams naturally try to stay ahead of the market. They lock in suppliers at advantageous prices when factors and signs seem to be pointing toward a potential disruption or a big increase in demand. However, the reality is that humans and typical software can’t account for all the variables in play. Their efforts essentially boil down to guesswork or discovering a trend after the fact—when it’s too late.

Predictive sourcing is now possible because of the advances in deep data, Artificial Intelligence (AI), and Machine Learning (ML) allowing procurement teams to be proactive to market changes and know when to source to avoid higher prices.

With so many systems now being cloud-based, a wealth of supplier data is available. This includes both current and historical data. In addition, real-time data is available for a huge range of variables that can impact the supply chain—everything from local weather conditions to currency exchange rates and product demand trends.

This is all great, but even teams of highly trained sourcing professionals equipped with typical procurement software will be overwhelmed by the sheer amount of data. Finding trends in this mass of data—which is changing minute by minute—in time to act on them is all but impossible.

At least it was until the arrival of predictive sourcing AI.

Predictive sourcing leverages the unprecedented processing power of AI and ML, turning the technology loose on the vast pool of supplier data and variables. Using predictive analytics in procurement, the results are forecasts covering suppliers and pricing. With predictive sourcing, procurement teams can anticipate outcomes with a high degree of confidence. They can be proactive in their supplier management instead of reactive.

How Can Predictive Sourcing Keep You Ahead of the Market?

As a member of your company’s sourcing team, what is the advantage of predictive sourcing? Can it keep you ahead of the market?

Let’s circle back to the global semiconductor shortage and its impact on the automobile industry. There are only several dozen chip fabrication plants in operation. A few companies dominate, with their fab plants making semiconductors under contract for other companies, which in turn sell chips through the supply chain.

Predictive analytics in procurement would have seen the warning signs converging last year:

• • • Increased demand for high-tech products across multiple sectors,
    • a new generation of game consoles launching,
    • geopolitical tensions resulting in Chinese companies buying up microprocessor stockpiles, and
    • chip fabrication plants starting to reach their maximum production capacity.

Of course, predictive analytics can’t anticipate events like a factory fire or chip production in Texas being disrupted by a winter storm. However, AI and ML would be able to see the impact of past similar events and their disruption to the supply chain and add that potential to its forecast model.

An automaker that employed predictive sourcing would have been able to act on these dramatic market changes before they happened. They would have moved quickly to lock up a semiconductor supply early in 2020. Instead of paying a premium—or running out of chips altogether—its assembly lines would keep humming. Instead of layoffs and lost sales, it would be shipping cars to dealerships to take advantage of the surging demand for new vehicles.

Learn More Predictive Sourcing

What’s the next step for your procurement team? How will you stay ahead of the market? Visit Arkestro to learn more about predictive sourcing and see how you can leverage the power of Arkestro to be proactive to market changes.