In continuation of our previous edition, in this final edition, we will focus on the technical architecture related to the solution, and the applicability of this solution on the use cases described earlier in this series.
We understand from previous editions how data is managed across multiple enterprise IT applications with multiple references to a specific transaction, though pointing to a single business event. This is primarily due to the lack of visibility of transaction audits centrally, leading to an underplaying of the value of relating those data sets for business purposes.
For example, it is important to know “who changed what on an order, and why?” due to which call-center personnel who are answering a call from an end-customer are wondering why an order/shipment is on hold. This could potentially be due to 3PL (3rd party logistics) providers putting a shipment on hold due to overweight restrictions. But this is purely recorded with details as a manifest audit in the logistics management application but not visible to other parties in the supply chain. Rather, a shipment audit on the order management and/or warehouse management applications does not record them at all resulting in a lack of visibility for personnel to answer customer queries, resulting in a negative customer experience.
The central visibility of business audits can be achieved traditionally by building many point-to-point interfaces with a lot of data duplicity over many applications in the enterprise. Over a period, this approach of such technical integration becomes complex, obsolete, and challenging due to these factors-
- Developing many point-to-point interfaces becomes very expensive from a roll-out and maintenance perspective for IT and business teams.
- Reconciling the data for matching and analytics also becomes challenging due to out-of-sync updates, interface message failures, and erroneous data production/consumption logic by publisher and subscriber applications.
- Re-platforming or upgrading any application (adopting technology trends) in the ecosystem will need the existing interface API to be deprecated and rewritten all over in line with the latest data grammar and technical nomenclature. Again, this is expensive from a development, regression, and roll-out standpoint.
- Inadequate insights into business health of transactions spanning multiple applications. (Most of the existing current monitoring solutions are around performance and siloed application monitoring)
The proposed point of view for solution architecture to overcome the above-mentioned challenges and limitations revolves around Blockchain to help achieve centralized data visibility through shared ledgers replicated across all applications(nodes) participating in the business. All parties have a copy of a single source of truth in terms of transaction audit which necessarily is secure, immutable, and consensus based. This, coupled with rest APIs for manageAudit (to create/upsert) and getAudit (for retrieval) modeled as microservices will make the solution scalable for consumption purposes.
Each of these APIs can be modeled as individual microservices which have specific push operations to Blockchain and consume from Blockchain. These APIs are now truly enterprise microservices that can be used by many applications in the IT ecosystem of the business to publish into Blockchain and consume from Blockchain.
Business audit data being post-facto of a transaction, it is unlikely that such data will be modified again to maintain the required immutability and tamper-proof security characteristics. This paradigm of business audits data makes it eligible to be on Blockchain. Blockchain possessing shared, secure, distributed, ordered, and write-proof characteristics is a very efficient way in the supply chain for business audits with ‘n’ parties to manage traceability and visibility of transactions and essential sequencing.
The below diagram is a point of view for enterprise audit microservice architecture. The solution is platform agnostic and can be hosted on-premise or on any hybrid cloud ecosystem.
Now for those of you wearing AI hats, integrating business agents such as voice-based search, chatbots, etc. with Blockchain-based business audits for consumption needs can spring interesting new use cases to solve. Happy AI thinking!
I hope you enjoyed these articles related to enterprise business audits from Acuver Consulting.
Author: Jagadesh Hulugundi
