Emerging Tech And The Digital Supply Chain

Shaily Kumar

Part 1 in the 3-part series “Digital Supply Chain for a Digital Economy

At SAP, we define an intelligent enterprise as an organization that uses data to achieve higher value outcomes – faster and with less risk. Sounds simple enough, no? But if you aspire to become an intelligent enterprise, where do you start? Look no further than your supply chain.

Supply chain processes are ripe for change – especially if you plan on surviving in the digital economy. The fact is, in a complex, globalized, digital economy, the supply chain of yesterday is not up to the task of meeting constantly shifting demand and increasingly complex supply networks. For a digital economy, what’s needed is a digital supply chain.

A digital supply chain uses data to manage supply chain processes from end to end – from detecting the initial demand signal sent by the customer and orchestrating supply partners to manufacture the item and deliver it to its destination. Agility, insight, and speed are all keys to success – and to rise to the challenge, intelligent enterprises are employing a range of emerging technologies.

Following are the key pillars of a digital supply chain capable of meeting the demands of a digital economy:

Internet of Things

With the cost of Internet of Things (IoT) sensors constantly falling, you can embed them in almost every item moving through your supply chain. This means you can track where everything is – all the time, in real-time. From parts for assembly coming from far-flung suppliers to finished goods en route to your customers, you can achieve literally unprecedented supply chain visibility.

IoT sensors embedded in the products you sell also provide insights into customer demand. For example, a pump exceeding vibration or temperature thresholds may need replacement parts – or a smart coffee machine on its twentieth brew may need a new order of beans. Based on this incoming data, an intelligent enterprise can quickly – and automatically – trigger the required supply chain processes.

Analytics

Massive volumes of incoming IoT data are of little use without the ability to analyze it quickly and respond effectively. To keep pace with real-time huge data volume management challenges, intelligent enterprises are moving away from siloed business intelligence approaches towards a well-integrated and orchestrated approach. No longer is historical data moved to a separate environment for analysis and reporting. Instead, it is brought together with live transactional data and held not on disk but in memory. This enables real-time analysis based on all of the data – and the triggering of alerts for taking action where action is needed.

Machine learning

With advanced analytics capabilities, you can use machine learning algorithms to detect patterns otherwise undetectable by human analysis, thus making the digital supply chain process intelligent in nature. This can help in multiple areas. You can analyze delivery truck patterns and optimize routes to ensure on-time service. You can analyze the health of warehouse machinery to predict maintenance needs. And you can combine customer demand data with supply availability data to optimize buffer stock positions – holding the contending issues of product availability and inventory-carrying costs in better balance.

Blockchain

Perhaps one of most potentially disruptive technologies out there today is blockchain. Though popularly associated with Bitcoin, blockchain is seen by intelligent enterprises as a critical enabler of the digital supply chain. Blockchain is a distributed ledger or database. Once a transaction is recorded on this ledger, users can view the transaction but they can’t change or delete it. The result is a permanent, inviolable record available to all with trust built in – without the need for intermediaries like banks or other trusted institutions.

What this means for supply chain people is greater transparency for any product that changes hands – from manufacture to sale. This creates visibility that helps reduce time delays, minimize costs, and eliminate the human error that often plagues transactions. Customers, for example, can confidently identify the provenance of fair-trade coffee beans – and upstream manufacturers can track the quality of incoming supplies and materials. And blockchain is far from aspirational. Already, companies like HPE are using it to ensure supply chain accountability toward goals of reducing greenhouse gas emissions.

At the heart of it all: a solid foundation of trusted data

The examples explored here are necessarily limited. The universe of use cases for how emerging technologies are used to optimize the supply chain is as wide and varied as the companies that employ them. But what’s bedrock across applications is a foundation of trusted data – a single source of truth that democratizes data throughout the enterprise for faster, more accurate decision-making. With a data foundation like this in place – coupled with a wide assortment of emerging technologies now readily available to organizations everywhere – intelligent enterprises can create a digital supply hain that delivers more value for the business and better outcomes for customers.

Stay tuned for the next blog in this series, where I’ll change my focus to look at how the digital supply chain changes life for customers on a daily basis. Up after that: a look at a specific event familiar to many readers – SAPPHIRE NOW – and how a digital supply chain can help make it even better.

For more information on how analytics can unleash the business value of the digital supply chain, read the new IDC Analyst Connection paper with Simon Ellis, program VP of IDC Manufacturing Insights.


Shaily Kumar

About Shaily Kumar

Shailendra has been on a quest to help organisations make money out of data and has generated an incremental value of over one billion dollars through analytics and cognitive processes. With a global experience of more than two decades, Shailendra has worked with a myriad of Corporations, Consulting Services and Software Companies in various industries like Retail, Telecommunications, Financial Services and Travel - to help them realise incremental value hidden in zettabytes of data. He has published multiple articles in international journals about Analytics and Cognitive Solutions; and recently published “Making Money out of Data” which showcases five business stories from various industries on how successful companies make millions of dollars in incremental value using analytics. Prior to joining SAP, Shailendra was Partner / Analytics & Cognitive Leader, Asia at IBM where he drove the cognitive business across Asia. Before joining IBM, he was the Managing Director and Analytics Lead at Accenture delivering value to its clients across Australia and New Zealand. Coming from the industry, Shailendra held key Executive positions driving analytics at Woolworths and Coles in the past. Please feel to connect on: Linkedin: http://linkedin.com/in/shaily Twitter: https://twitter.com/meisshaily