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Supply Chain Digital Reinvention: Optimizing to Meet Customer Demand

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The digital reinvention of the supply chain climbed the ranks of the corporate agenda in 2008, when the financial crisis hit. Back then, as revenue streams shrank, companies looked to their supplier networks to cut costs and boost efficiency. As a result, forward-thinking enterprises even began to optimize their supply chain data and bring in more analytics.

Organizations that took those steps are now enjoying a head start over competitors, given how important artificial intelligence (AI) is proving to be in retooling supply chains to deal with Covid-19-related disruption. What has become clear in recent weeks and months is that supply chain digital reinvention is very much on the agenda once again.

Respond to change

Looking back to 2008, the data show that demand unexpectedly collapsed across a wide range of industries. Today, on other hand, although we do see that pattern repeating in areas like travel and hospitality, in many sectors the opposite has been observed. Telecommunications is just one example of where demand has spiked, given the global shift to remote living and working. Companies able to facilitate that shift are also prospering. Video calling platform Zoom is a prominent case: the firm’s share price has rise rapidly, making gains which analysts believe will hold even when the world returns to working in offices.

Yet regardless of the particular direction of movement in demand for a firm’s product or service, what executives learned in 2008, and what they are now once again revisiting, is that supply chains need to be able to respond quickly to change. In the Covid-19 era this might mean finding and onboarding suppliers in a matter of days, either to meet a new customer need for online consumption, or to facilitate employees’ ability to continue working in lockdown.

For many companies, those scenarios will throw up unprecedented challenges, on top of those already imposed by working, unexpectedly, in a remote environment. Chiefly, enterprises now find themselves forced to identify not just one but often several new suppliers across locations and operational areas unfamiliar to them, and learn to work with them quickly in order to minimize the threats to business continuity generated by a crisis unfolding in real-time.

AI’s time to shine

Amid such turbulence, for many companies changes to supply chain networks are inevitable. But the more essential question to ask is: how many firms will change themselves – at the level of core practices and processes – as a result of the pandemic?

Innovators would argue -counter-intuitive thought it may seem – that a crisis is exactly the time to invest in new capabilities: unprecedented problems require radical solutions. In the case of supply chain digital reinvention, AI is a prime candidate to be that solution. The technology is poised not just to flourish amid the current disruption, but finally prove itself to every executive as a tool of long-term value.

To understand the potential impact of AI on the digital revolution of the supply chain, a look at any startup ecosystem is informative. To take Silicon Valley by way of example, we see a huge range of companies developing applications that are powered by the technology. These firms have created digital platforms that use AI to do a plethora of tasks, including analyze trade data, control warehouse robotics, track global shipments of goods, and forecast demand. Yet varied though these applications may seem, they share the common goals of increasing supply chain visibility and predictability. Those aims are achieved principally through the collection of data; vast amounts of data from sources previously inaccessible. With AI able to process all that information, enterprises are able to extract more insight than ever before from their procurement networks, and automate them to a much greater extent.

Supply Chain Digital Reinvention
Stages of automation in supply chain operations. As use of AI grows more sophisticated, enterprises can move from insights which are descriptive into ones that are prescriptive and cognitive. Source: Logility

Organizational DNA

But that is not to say supply chain digital reinvention is only about automation and replacing humans with robots. After all, even the most sophisticated pieces of software would have been unlikely to predict the size and severity of Covid-19 disruption. Nor would they have been able to provide all the answers any enterprise would need, at a time where on-the-ground realities are changing fast. Instead, AI is best seen as a tool that can go some way to alleviating the challenges inherent to all supply chains including poor visibility, bureaucracy, and uncertainty.

But even the best AI algorithms will fall short if the companies they are housed in are not ready to take full advantage of them. In practice, this means building and maintaining an information infrastructure, a framework that governs how a firm’s proprietary data is organized and processed so that AI engines can be applied to it for analysis and extraction of insights. Putting that data architecture in place is often referred to as taking the first steps on the ‘AI ladder’

Seen in this light, the adoption of AI for the digital reinvention of the supply chain is the catalyst for a more far reaching process transformation at the enterprise level. With procurement among the operational areas most affected by the Covid-19 pandemic, it is the ideal area in which to pursue an innovation agenda that can deliver tangible business value. Not only will that value be reflected in addressing immediate needs, it will also contribute to building a future-proof organization, ready to face the challenges still to come.


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