Data Management SPICE Service

Data Management SPICE at a glance

Turning Data into a Managed, High-Value Asset

In today’s connected and data-driven world, organizations collect, process, and rely on massive volumes of data. However, the real challenge is not the quantity of data — it’s managing its quality, consistency, and intended purpose across its lifecycle.

ZooKoo Consulting supports organizations in adopting and improving Data Management SPICE (DM SPICE) v2.0 – a framework developed by intacs® e.V. to assess and enhance data management capabilities in alignment with Automotive SPICE® principles.

Why Data Management SPICE?

Many organizations think they have a “big data problem,” when in fact, they have a data management problem.
DM SPICE helps establish a structured approach to treat data as an organizational resource — ensuring that data quality, lifecycle control, and governance become integral parts of business and engineering operations.

It provides a process-oriented framework to:

Ensure data integrity, traceability, and quality throughout the lifecycle
Enable cross-domain consistency for data-driven products and services
Support continuous improvement and maturity assessment using established ASPICE capability levels
Integrate with IT Services, AI/ML, and Functional Safety frameworks

DM SPICE v2.0 Process Model

The Data Management SPICE v2.0 model defines processes and practices that help organizations manage data as a valuable resource, across all lifecycle stages — from generation to disposal.

Data Management Process Group (MGD)

Process	Purpose
MGD.1 Data Management Scope and Business Case	Define the scope, stakeholders, and business case for data management activities.
MGD.2 Requirements for Data Management and Data Quality	Identify and manage stakeholder requirements for data and its quality.
MGD.3 Data Management System and Data Flow	Design and maintain data management systems and flows aligned with business goals.

Data Operations Process Group (DOP)

Process	Purpose
DOP.1 Data Integration and Deployment	Prepare and transition data and data systems into operations ensuring readiness and compliance.
DOP.2 Data Operation and Optimization	Monitor and optimize data operations, governance, and quality performance.

Supporting and Related Process Groups

DM SPICE leverages selected processes from Automotive SPICE® to ensure governance and improvement consistency:

SUP.1 Quality Assurance
SUP.8 Configuration Management
SUP.9 Problem Resolution Management
SUP.10 Change Request Management
MAN.3 Project Management
MAN.5 Risk Management
PIM.3 Process Improvement
ACQ.4 Supplier Monitoring
SPL.2 Product Release

Data Lifecycle Management

Effective data management extends beyond system implementation — it governs the entire data lifecycle, typically including:

Data Generation: capturing or creating data from systems, sensors, or users
Data Acquisition: ingesting and validating data for use
Data Storage: ensuring structured, secure, and retrievable storage
Data Processing & Usage: applying business logic, analytics, and decision-making
Data Archiving & Retention: storing historical data for compliance or analysis
Data Disposal: secure deletion or anonymization per regulatory requirements

Each phase is supported by DM SPICE processes to ensure the right data quality, accessibility, and compliance for its intended purpose.

Key Concepts We Implement

Concept	Description
Data Management	The coordinated processes, approaches, and resources to handle the value of “data” for a specific organizational scope.
Data Quality	The degree to which data meets defined requirements for accuracy, completeness, timeliness, and relevance.
Intended Purpose	The defined business or operational use case driving the data management effort.
Organizational Unit	The selected product, project, or service scope in which data management processes are applied.
Governance Framework	Policies, responsibilities, and practices ensuring sustainable control over data quality and lifecycle.

Example: Data Management in Connected Mobility

Connected vehicle systems rely on vast, dynamic data flows — from parking and navigation data to autonomous driving models. Using DM SPICE, organizations can:

Define data lifecycles and ownership between service providers and OEMs
Implement data quality controls for real-time updates and analytics
Establish traceable data governance across multiple platforms and suppliers
Prepare for AI/ML integration by ensuring reliable training data pipelines

1. Primary Lifecycle Processes

a) Acquisition Process Group (ACQ)

b) Supply Process Group (SPL)

c) Data Management Process Group (MGD)

d) Data Operations Process Group (DOP)

2. Supporting Lifecycle Processes

a) Supporting Process Group (SUP)

3. Organizational Lifecycle Processes

a) Management Process Group (MAN)

b) Process Improvement Process Group (PIM)

Our Business

Gap analyses

This is firsthand check of your processes with reference to Data Management SPICE model. In fact, here we focus the gap between "As-Is" vs. "To-Be". This service is provided by your intacs™ certified assessors

Consulting/Coaching

As recognized experts provide you best guidance with practical examples in order to improve your processes and your day-to-day activities to develop hardware system and component.

Process Definitions

We know, you are expert in development of your product and need to meet the customer deadlines. We are here to support you with our experts for defining your processes. Our experts with ample experience will first understand your working, and then will support you in process definition.

Pre-Assessments

Here our certified assessor checks your preparedness for going to formal assessment. More focus is to find out gap with target capability levels.

Formal Assessments

intacs™ certified competent or Principal assessor conduct formal assessment and provide rating to all the processes within scope of assessment.

Data Management SPICE