As consumer demand and buying patterns rapidly undergo changes in a digital economy, the supply chain that supports these emerging needs has to be both responsive and lean — and that’s a difficult balance to achieve.

The recent disruptions and demand-supply imbalances in healthcare due to the COVID-19 pandemic have further reinforced the need for a solution that allows all parties to be on the same page. The pandemic demonstrated that this need isn’t limited to retail alone, but is relevant to healthcare supply chains as well.

So where’s the most demand, what’s causing it, how can it be anticipated, and how can supplies be routed correctly?

The need for low-latency processes and information exchange is painfully apparent. Now throw in digital channel proliferation, with expectations of information and inventory being available on demand, and this quickly converts from a demand-supply problem to a real-time supply-chain visibility problem. The more we know, the more we want to know.

Emerging innovations in demand-sensing tools and frequent data sharing from retailers to suppliers and manufacturers have offered up new ways to meet these emerging demands. Now we need solutions that can bridge data islands across all sectors, to improve responsiveness while keeping costs of inventory down.

Can Smart Contracts and Blockchain Help?

Recently a new collaborative area of focus that emerged in the area of supply-chain provenance has promised the ability to track an item all the way from shelf to origin. A blockchain (a generic term we’ll use for distributed-ledger technology) based approach to provenance brings visibility to the end-to-end path that goods take. This capability was exactly what was needed during disasters such as the E-Coli outbreak in spinach, where the entire distribution was disrupted as the source of the problem was investigated.

Let’s examine the application of smart contracts to the broader demand-supply matching opportunity that the industry has been trying to address. To put this need in context, consider the case of routing healthcare and consumer supplies where there’s the greatest need as patterns change rapidly. Such enhanced responsiveness will also alleviate the need to maintain high counter-balancing inventory in the supply chain. In turn, that will allow enterprises to optimize investments toward business innovation and true contingency management.

Breaking Down Data Islands

The supply side responds to demand through a variety of forecasting methods that operate on the signals that are available.

On the one hand, to improve the flow of information, data sharing with suppliers continues to rise. Manufacturers are also investing in various demand-sensing and transportation optimizations.

On the other hand, signals on how the supply is shaping up and where it is can be used on the demand side to meet digital customer patterns across store or warehouse networks — for example, routing of inventory to the right locations, channel suggestions, and satisfying store network availability queries.

Problems being faced today due to information latency cascade along the supply chain and back:

• Demand signals are often delayed because it takes time to consolidate the patterns and make them available.
• The response is exacerbated by the delays in processing the demand and adjusting the supply plans.
• Finally, it takes time to actually make the inventory available at the right location, unless this latency is compensated for by higher inventory levels.

It follows that if forecast and demand signals were available more deterministically to the fulfillment and transportation parts of the supply chain, and vice versa, both responsiveness and inventory levels would be greatly improved.

One of the reasons latencies exist is due to the existence of disconnected islands of data that need to be constantly kept in sync. For example:

• A retailer building a data link of demand patterns for its suppliers must also first get the data from its operating units into the platform. This process alone is a series of data-management tasks to aggregate, reconcile, clean, enrich and finally distribute to the right recipients.
• Similarly, an enterprise that senses low inventory, places orders to suppliers, and then makes the delivered inventory available in its e-commerce system often must reconcile multiple systems such as enterprise resource planning, e-commerce and procurement.

This can be addressed by bridging process and data silos using smart contracts (mutualized business workflows) and perhaps blockchain (to maintain physical segregation of data stores between legal entities). In order to do that, we should view the end-to-end process as execution of shared business processes enabled by smart contracts that lead to a golden source of data, secured according to appropriate privacy, regulatory, and disclosure requirements.

The importance of using smart contracts to operationalize business processes can be understood by thinking in terms of harmonizing data islands within an enterprise.

Inventory as a Digital Asset

Let’s look at inventory in a different light. It’s moved across multiple parties, transformed and consumed in many ways, and provides benefits at each stage to different parties. If we consider inventory (to the granularity desired) as an asset, then the digital version of these assets is a representation of real things. We can call these “digital assets.”

With that in mind, smart contract-based models — for the very first time — can provide enterprises with a way to create and plug into shared business processes to manage these assets. Quite similar to the Central Bank Digital Currency discussions, it’s then a matter of tracking, consuming and replenishing these assets, rather than reconciling them post-facto across their custodial accounts.

Inventory processes have so far existed along organizational boundaries with a break every time a boundary is crossed. Let’s explore that a bit. Presently, every enterprise kicks off a business process based on an event triggered by data from someone else. For example, when demand data is received, a procurement signal is sent to suppliers that begins their analysis of stock availability; when a purchase order is received, the manufacturer begins its production; and when an invoice is created, the purchaser begins its validation and payment process. Multiple intermediaries, ERPs and procurement systems, applications and databases, and data-exchange methods such as APIs and EDI are used to facilitate these logically connected workflows. Each of them operates with inherent latencies, trying to stay in sync, and preparing for contingency based on historical patterns.

In a smart-contracts (and optionally a blockchain or distributed ledger) based model, these business processes can operate as unified multi-party workflows, thus giving the logical workflows a physical form. These shared processes then allow multiple parties to operate on a single definition of the underlying inventory in various stages, controlled by required privacy and disclosure requirements. For example, an update of sales data triggers supplier workflows, which can leverage their analytical algorithms to ensure on-shelf availability through appropriate warehouse and transportation routing that also share these unified workflows. No data transfer or signal transmission is required. It’s as if multiple parties are using a shared bus that exists within their own enterprise, but are able to see only the data they need to successfully execute their side of the bargain. This real-time visibility and shared business rules will generate tremendous efficiency and engage the entire supply chain. It eliminates reconciliation and process breaks that are common across application and enterprise boundaries.

This same architecture blueprint can be deployed to bridge data islands within an enterprise using smart contracts without necessitating a distributed ledger or blockchain. Smart-contract languages such as DAML can operate on blockchains and databases alike, which enables this flexibility.

The thinking so far has been centered around aligning and onboarding multiple companies on a distributed network. That’s because the traditional notion of a smart contracts-based architecture was based on the concept of blockchain nodes.

However, a more practical roadmap emerges if we consider that smart contracts-enabled workflows and the underlying persistence layer (blockchain or database) are independent of each other. For example, a first step in this direction could be for a retailer (or hospital, hotel or any other demand-serving channel) to convert its internal data-sharing infrastructures to be based on smart contracts-based workflows. That automatically affords each internal entity access to real-time, golden source data, while simplifying the data aggregation and reconciliation processes. Once this background for the data link has been prepared, then the platform can be extended to multi-enterprise collaboration using blockchain. In addition, this source of data can be used to deliver insights using conversational AI and data analytics for accelerated decision making.

Maintaining Competitive Differentiation

The use of such an architecture unleashes innovation, because individual players are still free to exercise their business decisions and profit-maximization recipes. The long-term value to each enterprise or application arises from how they play the game, not from spending effort on storing and mapping the rules of the game and the state of operations between participants. Thus, these mutualized workflows yield operational benefits and free up resources to create avenues for differentiation and customer value.

Our hope is that this analysis will help add to the discussion around some of the thorniest issues facing us today for demand-supply optimization. The ability of smart contracts and distributed-ledger technology to bridge data silos both within and across enterprises promises to be an important component of a larger solution comprising analytics and digital transformation.

We think of this capability as the enabler of a long-term, cross-business collaboration model, even within an enterprise. If we were to leave you with one takeaway it would be: Think in terms of mutualized business processes that bridge data silos and cut latencies in decision making.

Manish Grover is head of channel and solutions at Digital Asset. Rakesh Prasad is vice president of digital business at Innover INC.