Implementing Zero-Based Data (ZBD)
Zero-Based Data (ZBD) is an efficient method of how data is captured, managed, provisioned, processed, and consumed within an organisation. Please read earlier post to understand the concept of ZBD (2 minute read).
This is first of a series of posts on best practices to implement ZBD in large organisations.
To understand the approach to implement ZBD, it is necessary to identify areas in an enterprise data architecture that will have profound impact on the business.
Reference Enterprise Data Architecture components can broadly be grouped based on the type of activity that impacts the business i.e.;
Data collection/capture (Internal and External data stores)
Storage and management (Data Acquisition and Integration)
Provisioning for internal and external consumption (Data Propagation and Distribution)
Operational and business processing (BI and Analytics)
Moonshot projects (Artificial Intelligence)
In this article, let's explore the concept of ZBD for 1. Data collection/capture (Internal and External data stores) using a business scenario.
An insurance company leveraging blockchain and smart contracts to offer the insurance products.
Data can be collected in a business at various stages depending on the type of business.
It is evident from the the value chain the data is a crucial factor in executing a policy sell, underwriting, payments, claims, back-office ops, and re-insurance. The issue in the current insurance landscape is non-streamlined data movement through the value chain added to poor quality that is inadequate and irrelevant. This issue becomes a show stopper especially to implement new technologies such as blockchain and smart contracts since inadequate and irrelevant data will result in automated inaccurate execution of policies, claims and payments at scale.
Apply ZBD principles (relevance and adequacy) during initial data collection combined with a strict data quality rules and validation before the data persisted in the data store.
Where to apply the ZBD principles in the insurance value chain?
As described in the above diagram, ZBD principles for data relevance and adequacy can be applied at different value chain components of an insurance business.
Only relevant customer, product, and location must be collected to underwrite a policy
Only relevant customer, product, and location must be collected to verify a customer or to a create a new customer
Only adequate customer, product, and location must be exposed to re-insurers or authorised 3rd parties
It is crucial to implement a strict "Data Governance" to reap the benefit of ZBD which will be explored in separate article.
In the next article, we will explore applying ZBD for storage and management 2. (Data Acquisition and Integration).
To assess data capability and implement ZBD in your organisation, contact us at http://bit.ly/2ETLOpX