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Is Your Supply Chain Ready for Alexa? Artificial Intelligence? Autonomous Vehicles?

Autonomous trucks already speed down Nevada’s highways, and drones now deliver packages in China’s most remote villages.

Over the past decade, consumer products executives thoughtfully reinvented their supply chains to emphasize long, mass runs in standardized manufacturing facilities, aiming to lower costs and prices.

Now, those same business leaders face the challenge of overhauling their supply chains again, this time for a world being transformed by massive technology disruptions, as well as by the rising retailer demands and consumer expectations those technologies have created.

Company survey of 51 consumer products executives, we learned that 88% expect their supply chain and operations activities to feel the impact of digital technologies in the next five years, up from 66% just last year (see Figure 1).

Designing to win means painting a scenario in which the company produces its ideal product portfolio with the most collaborative supplier base, employing a perfect labor model and state-of-the-art production equipment, and delivering it via the optimal route to the customer.

The future scenarios need to take into account shifting ecosystems and profit pools, evolving consumer behavior and preferences, disruptive technologies, and new competitors and business models.

To illustrate the best strategies for supply chain reinvention, we’ll explore how companies can take a today-forward and future-back approach to three of these emerging technologies: artificial intelligence (AI) and machine learning, Alexa and voice ordering, and autonomous vehicles and delivery.

Increasingly, consumer products companies are using these technologies to squeeze inefficiencies out of their supply chains—ensuring that the right inventory is in the right place at the right time, for example, or reducing manufacturing costs with predictive maintenance intelligence.

When one company saw how its inaccurate demand forecasts led to excessive returns, it built a machine learning platform that drew on historical order and returns data to continuously improve demand forecasts at the SKU and store levels.

In the decades ahead, meal consumption will look vastly different, with companies using AI to create highly customized meals that consumers either buy online for delivery or purchase in supermarkets.

Meanwhile, companies like wellio are using artificial intelligence to provide customized meal suggestions based on personal health and taste preferences, selected recipes and ingredients consumers have on hand—gathering and interpreting data over time to further understand home chefs’ preferences.

As these shifts play out over the next 10 to 15 years, brands will need to reconfigure legacy supply chains that were built for mass scale, creating new models capable of handling both mass scale and customization.

And they will move to much more flexible manufacturing systems, including designing and running smaller manufacturing lines—in some instances, even adopting an extreme asset-light model, outsourcing all manufacturing to nimble third-party manufacturers.

Another big step they are taking: adopting specialized labeling and shipment-friendly packaging to improve operational efficiency and the consumer experience (measured through a combination of user reviews and user returns).

Some are also considering new pathways to shoppers, such as direct-to-consumer businesses, that will help them stay relevant by generating valuable customer data, thus gaining a defensible position against the Amazons of the world.

The company began providing differentiated levels of service based on the importance of the customer as well as its ability to collaborate for mutual gain.As a result, it expects to deliver best-in-class on-time/in-full delivery to priority customers while reducing inventory by 20% and lowering total network costs by nearly 15%.

“Earlier this year we introduced a range of new razor products and declared that ‘one size’ does not fit all men when it comes to razors,” said Pankaj Bhalla, P&G’s director for Gillette and Venus North America, in an online statement, adding that the pilot program furthers the company’s commitment to place power in the hands of consumers.

Artificial Intelligence is coming whether we are ready or not

The analyst firm Gartner predicts that while AI will automate 1.8-million people out of work by 2020, it will create 2.3-million new ones, a gain of 500,000.However, these new jobs will only be available to those with the right set of skills.

We are piloting new ways of transmitting knowledge which, when perfected, will play a vital role in preparing our people to transition to a new type of job, likely to be one that will involve the higher value, relationship-building service end of the business.

It is no longer only about what you know at any given point, but rather how quickly you can adapt and learn.It will take planning and innovative thinking to overcome the challenges of helping the existing workforce to transition, and to ensure the educational system produces the right skills.

Artificial Intelligence: Is your business ready?

Science fiction writers have long speculated about the development of intelligent machines and, as the pace of technological progress quickens, reality is catching up with fiction.

For example, recent years have seen computers score their first victories over human professional players at the fiendishly complex board game, Go.

Getting ahead of the AI curve Despite these impressive statistics, and the sometimes dramatic headlines about AI, other evidence suggests that many businesses are unprepared for the challenges and opportunities AI will bring.

While 72 per cent of business leaders recently surveyed by PwC believe AI will be fundamental to the future, just 15 per cent of enterprises are using the technology currently.

Whether you are an automotive company readying itself for the ascent of intelligent self-driving cars and smart-cities where algorithms optimise traffic flow, or whether you are a bank using AI to analyse customer data and develop ever more personalised services –

Although this approach is sometimes sufficient for traditional software, which is programmed entirely by humans, it will likely prove to give inadequate protection for the machine learning techniques that are the foundation of the AI revolution.

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