The Value Proposition Assessment tool - VPAt

This paper proposes a simple approach/tool (VPAt) for identifying the value propositions of explicit data management domains for stakeholder business imperatives.

Background

Data management frameworks are traditionally unrelatable to anyone other than highly capable data practitioners who themselves often struggle to articulate the business implications of good data management practices.

By qualifying up front the business imperatives for which data management practices are relevant, and understanding the perspectives of stakeholders that care most about each of the business imperatives, it is possible to present the stakeholders with a compelling and enticing data management story.

The assessment

The value proposition assessment derives from two overlapping sets of information:

Stakeholders/Involved Parties and their business imperatives
Data management domains and the business imperatives they alleviate

Once these two sets of information have been coarsely determined the refinement of value propositions takes place by iterating through both sets in increasing detail. Two or three iterations is usually sufficient to present well-defined value propositions to specific stakeholders.

Each information set can be represented as a table:

	Business imperatives
Stakeholder classes	Mappings

And

	Business imperatives
Data management domains	Mappings

Analysis needs to be conducted at xx points:

Determine stakeholder classes – these should be known
Determine business imperatives – these should be known
Determine data management domains – these are dependent on the data management framework being considered
Determine mappings between stakeholder classes and business concerns – straightforward for business people
Determine mappings between data management domains and business concerns – straightforward for data practitioners

Iteration involves increasing the granularity of the business imperatives and perhaps the granularity of the data management domains.

Applying the framework

Identify the stakeholder or involved party based on their relation to business imperatives:

		Business imperatives
		Performance	Risk	Cost	Innovation	Open by Design
Stakeholders and Involved Partners	Public	Primary		Primary		Primary
	Ministers	Primary	Primary	Primary	Primary	Primary
	Govt System Leads	Primary	Primary	Primary	Primary	Primary
	CEs	Primary	Primary	Primary	Primary	Primary
	DCEs	Primary	Primary	Primary	Primary	Primary
	GMs	Primary	Primary	Primary
	Practitioners	Primary	Primary
	Data Analysts	Primary	Primary		Secondary
	Data Administrators	Primary	Primary
	Proj/Prog Managers	Primary	Primary	Primary
	Developers	Primary			Secondary	Secondary
	Classifiers	Primary
	Architects	Primary	Primary		Secondary	Secondary
	Business Analysts	Primary			Secondary
	Partners	Primary	Primary
	Suppliers		Primary	Primary	Primary
	Regulators		Primary

There are several ways to factor data management as a whole. This assessment employs the Government Enterprise Architecture for NZ (GEA-NZ) Reference Framework as the guiding context.

Government Enterprise Architecture for NZ Reference Framework – Digital.govt.nz

GEA-NZ includes eight dimensions which are organised here under five data-centric domains:

Data Strategy (requirements): Strategy, Investment, and Policy
Data Architecture (definition): Standards; Application and ICT Services; Infrastructure
Data Governance (provision): Governance and Performance
Data Operations (execution): Business; Identity, Privacy and Security; Standards
Data Quality (assurance): Standards

These data domains are tabulated against business imperatives to identify value propositions. Each of the mappings needs articulation as a data domain value statement (This data domain provides value “By…”) and this is best completed by a business-oriented data practitioner.

		Business imperatives
		increases Performance (Deliverables)	reduces Risk	reduces Cost	increases Innovation	supports Open by Design
Data Domains	Strategy [requirements] Strategy Investment Policy	By requiring a clear investment roadmap that delivers the right data-dependent capabilities at the time the business requires them	By requiring the identification and documentation of data, related processes and systems so that risks can be explicitly managed	By requiring a comprehensive view and understanding of data-related investment and expenditures	By requiring environments and platforms for data to contribute to the development of new opportunities	By requiring architecture and governance suitable to establish an open data mindset, practice and culture
	Architecture [definition] Standards Application & ICT Services Infrastructure	By defining the changes in data, data-related process and systems to deliver business objectives	By defining data, data-related process and systems to reduce complexity	By defining data, data-related process and systems to increase certainty of investment and expenditures	By defining environments and platforms for data to contribute to the development of new opportunities	By defining environments and platforms to contribute to an open data mindset, practice and culture
	Governance [provision] Governance & Performance	By providing consistent authorisation, definition and description of data, related processes and systems	By providing clear accountabilities for data, related processes and systems	By providing a mechanism for controlling data-related investment and expenditures	By providing the environments and platforms for data to contribute to the development of new opportunities	By providing the environments and platforms to contribute to an open data mindset, practice and culture
	Operations [execution] Business Identity, Privacy & Security	By operating the business effectively	By responsibly executing business activities	By operating the business efficiently	By improving efficiencies, so that resources can be released to increase opportunity	By providing the context for maximising the use of data throughout its lifecycle
	Quality [assurance] Standards	By providing fit for purpose, accurate and trusted data for evidence-based decisions	By minimising risk to the reputation of the organisation	By minimising data maintenance costs	By enabling the organisation to maximise value and opportunity of data assets	By instilling a high level of confidence in data available for re-use

It is now possible to make statements like:

“Ministers, Agency leadership, operational staff, and partners care about data quality because it reduces risk by ….”

A business lens for targeting data maturity assessments

The set of value proposition statements resulting from the application of the VPAt to relevant business imperatives can be used to inform the selection of a relevant maturity assessment and then to target specific areas of measurement within that assessment. The VPAt increases the likelihood that the measures identified for maturity analysis are congruent with and can be linked directly to particular organisational business objectives.

Because the data domains used in the VPAt draw from the same architectural reference model (GEA-NZ) as the DIA Generic Business Capability and DIA Data and Information Governance maturity models (Figure 1), there is an especially strong alignment between the value proposition statements and the set of DIA measures designed to characterise organisational data maturity.

This provides a level of analytical consistency that expedites a clear line of sight throughout the data maturity assessment process and facilitates meaningful outcomes.

Radar graphs containing the capability domains of business

Figure 1. DIA Generic Business Capability Model

A radar graph containing the domains of the data and information governance maturity model.

Figure 2. DIA Data and Information Governance Maturity Model

However, if other data maturity assessments – for instance those offered by third parties or those for open data or geospatial data published by New Zealand government - are deemed valuable, the VPAt outputs can also be used to develop an approach for growing organisational data maturity in those areas.

In this way, the VPAt can serve as a lens to focus organisational efforts on developing those data management capabilities that provide the highest level of support for business imperatives. Meaningful baselines can be established and a potential maturity path designed to not only support business objectives generally, but furthermore to provide a powerful means of demonstrating the critical business value of good data management practice.

Supporting organisational operating models

The VPAt value proposition statements, in conjunction with data maturity assessment results, are available to inform organisational operating models and facilitate successful data outcomes (Figure 3).

Value statements can be employed directly in the development of data-related business cases, strengthening the proposition for investment in organisational data assets and capabilities.

In addition, they can help target the selection and optimal use of data maturity assessments, ensuring that assessment activities are meaningful, manageable and maintain a clear line of sight to business imperatives.

In this way the outcomes of a data maturity assessment, including baselines and sets of progress measures, are more likely to provide real business value. With an intentional alignment to organisational business imperatives, assessment outcomes are well positioned to inform the development and implementation of data-related action plans and provide a structure for reporting.

A flow diagram which demonstrates how the VPAt fits alongside the organisational operating model and the maturity assessment models.

Figure 3. The VPAt supports organisational operating models, informing business case development and targeting the selection of maturity assessments which can be used to inform action plan design and reporting.

Contact us

If you’d like more information, have a question, or want to provide feedback, email datalead@stats.govt.nz.

Content last reviewed 16 July 2021.