The Intelligent Automation Imperative: Taming Supply Chain Complexity

We create 2.5 quintillion bytes of data every day, according to Forbes. Global supply chains are responsible for a good portion of these data. Transactions in sourcing, manufacturing, logistics and distribution generate hundreds of millions of data points. This data volume is representative of today’s supply chain complexity – and it’s increasing. Thousands of SKUs, hundreds of transportation lanes and countless business partners must be managed in tandem to optimize business performance and serve the end-customer.

The sheer volume of data can be overwhelming, but if leveraged effectively, all of this data can help tame today’s supply chain complexities – even turn supply chain into a competitive advantage. It all depends upon how we use this data.

Intelligent Automation: Build the Digitization Puzzle One Piece at a Time

Supply chain and logistics leaders are investing in digitization and automation. The Intelligent Process Automation Market is expected to reach $8 billion by 2023, growing 40 percent, according to Market Research Future.

The challenge is that many leaders are thinking of digitization as a single step that will reap grandiose – and often unrealistic – results. Instead, think of digitization as a puzzle: each piece plays a critical role, but you can’t put the puzzle together in a single move. The puzzle looks nicer with every piece, but the final picture takes commitment, flexibility and patience.

Building an effective intelligent automation (IA) capability requires a step-by-step approach, with each step tied to tangible business outcomes.

Smart workflows facilitate human-machine interactions enabling real time visibility, tracking and proactive management of end-to-end processes. RPA automates repetitive, mundane tasks that are best suited for software. Machine learning and advanced analytics identify patterns and emulate logical thinking which provides insights and recommendations at the user’s fingertips.

With low cost, off-the-shelf technologies readily available to assemble the digitization puzzle the ball is now in the ‘business court.’ Supply chain leaders need to choose their use cases and crystalize the business impact.

Digitization Use Case: Logistics Exception Management

For example, let’s consider a common supply chain headache – logistics exception management. Importing a widget, drug or fruit that is produced abroad can face several exceptions, and a typical one is customs holds due to missing or incomplete documentation. Today a pack of documents needs to accompany a shipment for import clearance – documents can be in the box, on the box, sent electronically, handed to brokers, etc. There are several potential failures points that can quickly downstream operations.

At the simplest level, digitizing logistics transactions on an orchestration platform can make shipping documents available on-demand and can alleviate the need for paper-based processes. Supply chain partners can increase visibility throughout the product journey and can drive multi-party collaboration. Everyone can see what’s happening, in real time, which makes it easier to spot and resolve exceptions like missing information.

This may seem basic, but remember, the name of the game is incremental improvement. Today, supply chain data is typically housed in multiple, disparate systems. Shippers, suppliers, carriers, forwarders, brokers and others lack a ‘one-stop-shop’ view to visualize, analyze and act on data. So, digitization, in this sense, represents a solid improvement with several business benefits – reduction of mistakes, duplicate work, delays, shipping costs, stock-outs, inventories.

The automation possibilities grow from there. For example, once everything is digitized, AI-powered algorithms can automatically predict potential obstacles and trigger an automated workflow to remedy the situation before it occurs, all through a human-machine facilitated process.

Over time, the digitization capability matures and data turns into intelligence that then enables smarter decision-making. Scenario modeling and recommendation engines enable organizations to solve bigger problems. AI and smart workflows automate more processes, freeing supply chain professionals up to focus on the customer, innovate and drive revenue lift.

The Die is Cast: The New Human-Machine World is Emerging

The biggest future impact on revenue and company growth will occur through the digitization of supply chains as reported by McKinsey. However, the survey reports that only two percent of its respondents have a strategic focus on digitizing their supply chain right now. So why is there a disconnect?

On one end, the investment focus has been on digitizing the consumer experience – and rightfully so thus far. On the other end, progress in digitizing the supply chain has been impeded by the existing ‘technology debt’ – meaning outdated, inflexible, ‘user-hostile’ software.

Business expectations are changing, and now is the time to bring the consumer ‘Amazon-like’ experience into enterprise supply chain software. Think how the one-click purchasing experience with recommendations can apply to let’s say, logistics exception management. A logistics manager seeing predictive insights about which shipments are at risk, which ones to prioritize and even what is the next best action to proactively mitigate an exception – all that with one click on her mobile app.

This is the symbiotic human-machine relationship that consumers are now used to – even without fully recognizing in some cases – and are now expecting in the work environment as well. The dye is cast, a new era is emerging for supply chain and the key is modern enterprise software. Software that stands up quickly to solve tangible business problems, while simultaneously paving the ground to the next generation IT architecture for the enterprise. Spearhead the change into digitizing your supply chain and start reaping the benefits now.