An organization’s business capability rests upon the efficiency of its Procure-to-Pay process, especially for companies that procure raw materials, transform the raw materials in some way and sell the finished goods in the market. The Procure-to-Pay cycle encapsulates all the steps involved in obtaining raw materials from the supplier - right from planning the quantities up to reporting the cost of production. Technology is being continuously enhanced to out-perform manual efforts in each step of Procure-to-Pay. Organizations are probing into each innovation to determine the best-fit solution for streamlining the end-to-end process. This article looks at how disruptive technologies, such as Artificial Intelligence (AI) and Blockchain can help transform the Procure-to-Pay process.

Procure-to-Pay, at its as-is stage, is riddled with inefficiencies –  ranging from invisible costs, excess inventory pile-up, to rapidly changing compliance and regulatory norms, lack of management visibility in day-to-day operations, complex vendor communication process, etc. These inefficiencies are a result of the lack of focus on technology at both management and grass-root level that can enable a business to be a master of its data, in all forms and levels of hierarchy.

The problem, in itself, is universal – ⁱdata is polymorphic, rapidly changing, multi-sourced, and asynchronous. On the other hand, the solution demands tailoring to business-specific data and operations. Businesses struggle to adopt technology that is capable of addressing all of its problems in one go, while technology struggles to give its best possible output from incomplete data, uninformed handlers and inefficient processes. ⁱⁱOrganizations are also prone to fall into the “me-too” trap – investing in technology that doesn’t necessarily fulfil its requirements to the T, blindly following the industry trends.

To effectively resolve the problems plaguing the Procure-to-Pay cycle, the industry needs an integrated platform that addresses both the diversity of data and the specificity of business needs. We need a solution that is capable of “intelligently” identifying the changing data and handling it accordingly, while at the same time “breaking the silos” in business processes to provide the much needed common ground. It is here that technologies, such as artificial intelligence and blockchain can prove to be useful. ⁱⁱⁱA blockchain solution is capable of strengthening the audit trail, providing transparency, quickening settlement process, and increasing security. The AI component can enhance data processing and analysis to enable seamless performance from the blockchain, as well as provide never-seen-before insights to the management, both from the perspective of performance of the supply chain and performance of the solution being used. ^ivEnlisted here is an ideal scenario:

1. The proposed solution would onboard the vendor/s of the organization into a blockchain, only after a successful E-KYV (Know Your Vendor) procedure against the selected vendor/s. That E-KYV solution would be capable of intelligently performing supplier risk management services by aggregating, investigating, analyzing (using advanced machine learning algorithms) and verifying vendor data.
2. Once through the screening process, the vendor can join the private, permissioned ^vEthereum network. But why would the vendor agree to join? Incentives for the supplier include servicing non-local clients better, quicker invoicing and faster payment receipt. Ethereum is preferred over other blockchain networks because of its superior smart contract and privacy features.
3. Once in the blockchain, the vendor and the business would create^vi a “smart contract” to facilitate each and every term of the agreement.
4. In the future, whenever a Purchase Requisition (PR) is placed, the smart contract of the blockchain network would be updated with financials and volumes from the PR.
5. Post its approval and acceptance by the vendor, the PR is converted to a Purchase Order (PO), which is updated into the blockchain for access by each party.
6. The Sales Order from the vendor adds additional clauses to the Smart Contract – like expected delivery date, actual price, etc. The status of the order is always visible to all parties at all times, providing complete transparency, and immediate identification of anomalies in the process.
7. Post this, every action related to the order would update the smart contract – namely, when the goods are dispatched and received, invoice updated and final payment done

The business can use cognitive spend analysis and revenue prediction to achieve maximum revenue and minimum leakage from the transaction. This roadmap leverages the best of both artificial intelligence and Blockchain, making both work in tandem to leverage the best out of the other. In other words, artificial intelligence provides insights on how increased visibility is benefitting the stakeholders in the Blockchain, and Blockchain helps AI solutions by getting instant, and near perfect data to process.

Small and medium scale technology providers are proving to be pioneers in developing such platforms for industries in dire need of these solutions. Eight out of 25 “Forbes Most Innovative AgTech startups in 2018^vii ” use artificial intelligence to solve problems plaguing agriculture, while three of those eight use blockchain to manage the supply chain of their clients. This coming from the agricultural sector, which is dominated by manual processes and traditionalist outlook, speaks a lot about the far reaching effects of technology. The case in point is a  ^viiiglobal coffee supply chain that uses Image recognition AI to identify superior coffee beans from the others and grade the beans as per its quality.  ^ixBlockchain then ensures quick payment resolution for farmers and records all aspects of the transaction for all parties involved, viz., the farmer, the co-operative and the purchasing companies.  ^xThen, data on quality and productivity can later be used to analyse the effectiveness of the supply chain.

Blockchain, in conjugation with artificial intelligence, is leading the Industry 4.0 revolution and is solving complex business problems that shall alter the technology topography of the world. Navigating the complexities of newer technologies can be challenging, but enterprises are increasingly discovering new business applications that were previously unknown or unexplored. To maintain their competitive edge, organizations must undergo a cultural shift and encourage their employees at each level to find new opportunities where technology such as these can be employed to drive the 3Es – efficiency, economy, and experience.

References:

ⁱhttps://www.hfsresearch.com/pointsofview/triple-a-trifecta-automation-analytics-and-artificial-intelligence

ⁱⁱhttps://www.techemergence.com/enterprise-adoption-of-artificial-intelligence/

ⁱⁱⁱhttp://www.idrbt.ac.in/assets/publications/Best%20Practices/BCT.pdf

^ivhttps://www.emc.com/collateral/software/15-min-guide/h4824-15-min-contract-lifecycle-mgmt-gd.pdf

^vhttps://blog.codecentric.de/en/2018/04/blockchain-application-fabric-composer/

^vihttps://blockchaintrainingalliance.com/blogs/news/ethereum-vs-hyperledger

^viihttps://www.forbes.com/sites/maggiemcgrath/2018/06/27/the-25-most-innovative-agtech-startups-in-2018/#2599beb12302

^viiihttps://store.hbr.org/product/coda-coffee-and-bext360-supply-chain-machine-vision-ai-iot-and-blockchain/tb0539?sku=TB0539-PDF-ENG

^ixhttps://venturebeat.com/2017/04/11/bext360-aims-to-transform-the-global-coffee-supply-chain-with-blockchain-and-ai/

^xhttps://www.bext360.com/

Shruti Banargee

Senior Executive

Shruti Banargee is a Senior Executive for HOLMES - Wipro’s Artificial Intelligence & Automation Platform. She handles PMO for HOLMES and Automation Ecosystem. She is an MBA from VGSoM, IIT Kharagpur.