Streamlining Global Trade: How AI-Enabled Business Networks Can Make Your Business Smarter
We hardly need reminding of the global challenges facing companies today, from increased competition from low cost foreign competitors, to tariffs and changing regulations. As if that weren’t challenging enough, there is the need to keep abreast of technology innovations such as digital business networks, artificial intelligence and blockchain, that are giving startups the opportunity to leapfrog more traditional and mature companies. Within this landscape, companies need to transact with more and more companies, using different systems and often in different time and regulatory zones, which increases the complexity of doing business exponentially.
So, how do you address these issues while modernizing and continuing your business?
Digital Transformation or Consumer-Driven Transformation?
Fundamentally, conducting business is about supplying to the demand of the end consumer. Businesses that win are the ones that create demand with innovative products; or, better serve existing demand. Regardless of the approach, successful companies also understand that they need to be sensitive and responsive to customers’ needs and the market.
Technology serves a vital role as the means by which businesses register demand, plan, forecast, make, move and sell products and services. Technology can make or break a company’s ability to react to changing consumer demand, market shifts, and supply constraints. It can also limit a company’s ability to fully exploit the innovative technologies that are constantly emerging.
For example, most companies are split into functional silos. This is partly corporate culture and partly technological, thanks to the typically inward-focused nature of enterprise systems. Whatever the causes, silos inhibit visibility, speed and agility. Steven Bowen, in his book Total Value Optimization, calls silos “one of the most pervasive and profound barriers to real competitive advantage in every company.” This problem is multiplied across the global business footprint and across the worldwide supply chain, with regions, countries and trading partners having their own systems and silos.
For optimal functioning, all departments need to align around the corporate strategy, and all trading partners around the same objectives, with the primary concern of serving the end customer as effectively as possible. After-all, it takes just one weak link to drag down the performance of the whole supply chain.
Networks Break Out of the Box
We can learn a lot from disruptive leaders in today’s world, as companies like Uber and AirBnB have each disrupted their respective industries because of their ability to sense and respond to consumer demand and match it to supply in real time.
For instance, Uber leverages a multiparty network where all drivers and riders connect to a single platform and drivers are routed to riders, automatically. What’s more, you use the same platform to summon your ride (or your stay in the case of AirBnB), make the contract and transact payment, and rate the other party. Both are “end-to-end” platforms that handle all aspects of the search, booking, payment and review processes. They make the whole process seamless and provide value for both buyer and seller.
The multiparty networks at the heart of these types of businesses, are creating huge efficiencies by eliminating delays and costs and connecting all parties in real-time with a single, authoritative version of the truth. No silos, no delays, no confusion; just a frictionless network for transacting with anyone, anywhere, anytime.
Intelligent Business Networks
The opportunities for business-to-business companies are even greater, because the buyer-seller-mover relationships are complex and multi-layered. There are many more silos, blindspots and delays in a global supply chain compared to a simple one-to-one relationship of rider to driver as in Uber, or guest to homeowner as in AirBnB.Thus, a multiparty network that connects all seamlessly in real-time, has a much bigger impact. Instead of a business partner waiting days or weeks for information to flow upstream, they get it instantly and can react immediately. If a customer’s promotion is selling more than expected, a supplier with visibility to sales can proactively plan for increased orders and ramp up its own supplies and production.
And it gets better. Advanced multiparty networks not only share data, provide real-time visibility, and enable business partners to collaborate as events happen, they also leverage technologies like artificial intelligence and machine learning to optimize and automate processes. “Intelligent agents” monitor conditions across the supply chain, things like sales data, inventory levels, orders, shipments and how they relate to critical milestones. They can predict sales and identify trends and anomalies.
Because all business partners are on the same network, intelligent agents are able to not only flag potential issues, but actually intervene to solve them. They are able to continuously reconcile sales data with projected inventory levels, shipments from ocean and domestic carriers, along with actual lead times, to predict supply and demand issues in advance and then execute proactive solutions to avoid them.
With the vast amounts of data flowing across the network, these systems are ideally suited to machine and deep learning, enabling them to identify patterns and correlations. This data can then be used to predict sales and cascade the order forecast back through the supply chain through distribution centers, manufacturers and suppliers. They continuously monitor the sales and inventory in near real time, and can foresee issues like pending stock out swell in advance. Intelligent agents can then resolve them by autonomously reallocating supply from DCs to stores, adjusting forecasts, creating new orders and helping manage logistics processes.
Better yet, the system monitors the outcomes of these autonomous actions and recommendations, and continuously “learns” and adapts to recommend and execute the most effective resolutions to similar problems in the future.
Data-Driven Agile Ecosystems
This is merely a glimpse into the nature of these emerging intelligent business networks, as they are evolving rapidly. Unlike traditional systems, they are able to harvest new and unstructured types of data, such as weather, traffic, social media chatter and more.
The volume of data in today’s supply chains is set to explode with the increasing use of sensors and live streaming data from containers, vehicles, handheld devices and industrial machinery.
While the sheer volume of data is overwhelming for human managers and for traditional systems, it is ideal for multiparty networks with machine learning algorithms and intelligent agents. They can learn from it and extract new insights that can drive better operations, higher service levels to customers and lower costs for all automatically, and often without the need for human intervention.
Multiparty networks are smarter, enable easy onboarding of trading partners (with a single connection) and provide pre-built solutions with PaaS tools that enable rapid tailoring and extension of functionality to suit changing business needs. Further, the multiparty network model makes it easy to consume both legacy data and leading-edge data from technologies like IoT, product authentication, 3D printing, and blockchain.
It is often said that intelligence is really the ability to adapt to change. Multiparty networks are built to be adaptable through and through. For instance, connections between trading partners are virtual and thus easily reconfigured should trading relationships change. The permissions controlling each trading partner’s rights over visibility and execution on each specific data object is configurable and can easily be turned on and off through a simple user interface. Old and new technologies can co-exist, with multiparty workflows coordinated across different systems and parties. Software developer kits make it easy to adapt existing network solutions or build entirely new ones on the platform.
The result is an extremely adaptable network platform, supporting an agile ecosystem of all trading partners centered on serving the customer at the highest service level at the lowest cost.
About the Author
Nigel Duckworth is a marketing strategist at One Network Enterprises, provider of a blockchain and AI-enabled network platform that enables all trading partners to transact in real time. To learn more, visit https://go.onenetwork.com/article-one or follow them at https://twitter.com/onenetwork