Zero-Based Data (ZBD)

Just as Zero-Based Budgeting (ZBB) is re-emerging as the efficient process for allocating and provisioning funding, Zero-Based Data (ZBD) will be the future of how data is captured, managed, provisioned, processed, and consumed within an organisation.

'Zero-Based Data (ZBD)' is a term coined by Shen Pandi (Founder of Derisk360) in 2018.

ZBD is a term for data capture, management, provisioning, processing, consumption to be adequate, relevant, and limited to what is necessary within an organisation.

A brief history of ZBB

ZBB first rose to prominence in the government during the 1970s financial crisis. Faced with mounting public pressure, U.S. President Jimmy Carter promised to balance the federal budget and reform the federal budgeting system using ZBB, which he had used while he was governor of Georgia. Though it was initially well received, ZBB proved not only complicated and time consuming, but also ineffective, as it was Congress and the executive branch that were ultimately responsible for deciding whether to keep or eliminate a program. Additionally, the president’s budget office used a variant of ZBB as agencies were asked to rank their programs within funding limits. This forced the agencies to assign priorities and identify possible reductions. *

Rising popularity of ZBB

ZBB has recently experienced a resurgence of interest in both the public and private sectors. In the public sector, this stems largely from contemporary fiscal constraints precipitated by the 2008 recession. Facing budget cuts and due to an increase in public scrutiny, government agencies have started using alternative budgeting methods such as ZBB, instead of more traditional budgeting methods such as incremental budgeting.*

Adequacy

Sufficient data to fulfil the intended purposes

Limitation Relevance

Review the data held, and delete Collect only the necessary data

anything unnecessary for the specified purposes

Mapping of ZBB principles to ZBD

1. Budget is not connected to previous year spending ---------------------- Adequacy

2. Spending increases or cuts are not simply spread even across budgets ------ Relevance

3. Budgets are tied very specific activities and levels of service --------------- Relevance

4. Funding is targeted more to activities that align with the strategy ----------- Limitation

Key issues with current data provisioning and processing approach

1. Not asking right questions to the users about data provisioning

2. Start with data that already exist that may be more than what is required

3. Duplication and data redundancy due to above stated reason

4. Lack of diverse data sampling

5. Non-existent or inefficient archival and audit mechanism

Best practice to implement ZBD

• Establish a robust governance reporting to the Chief Data Officer

• Map all data lineage to the consents for data subjects

• Establish a global metadata and business glossary linked to data lineage

• Report audit of the ZBD 'Key Performance Indicators' (KPIs) to the senior management

Benefits of ZBD

• Resulting data usage is well justified and aligned to data privacy and GDPR strategy

• Accelerate broader collaboration across the organisation

• Supports cost reduction by avoiding automatic under-utilised data volume increase

• Improves operational efficiency by rigorous challenging of assumptions

To assess data capability and implement ZBD in your organisation, check out our GDPR Assessment or contact us. http://bit.ly/2voT3iC

* Source: Deloitte

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