Infinitive’s Data Maturity Assessment evaluates your organization's maturity level in the realm of data analytics against the essential elements that make an organization data-driven and mature in its usage and analytics capabilities
Measure Learning Case Study
Head of Product, Major Healthcare Analytics Organization
Today companies are struggling to keep pace with the rapidly evolving landscape of the industry. The world has entered an era driven by data, where competitors gain an edge by harnessing advanced analytics, AI, and machine learning. Recognizing this new reality, companies are finding several significant challenges such as the rise of cyber-attacks, increased regulations, and common cloud implementation and compliance challenges.
This detailed analysis is designed to guide organizations in assessing their maturity level in the realm of data analytics. The survey is grounded in five foundational pillars – Strategy and Sponsorship, Data Management, Technical Foundations, Talent and Skills, and Value Creation. Each pillar evaluates the essential elements that make an organization data-driven and mature in its data usage and analytics capabilities.
Infinitive’s data maturity methodology serves as a comprehensive guide, providing a structured pathway that aligns with industry best practices. Each component or pillar of the methodology addresses specific areas of concern and has been crafted with real-world complexities in mind.
Strategy & Sponsorship
Does the organization have an established vision and sponsorship at the senior leadership level for analytics to have a strategic impact?
Key Components
Data
Management
Does the organization formally manage it’s data assets to maintain
quality and enable effective use in
analytics?
Key Components
Technical Foundations
Does the organization have a modern technology foundation underpinning its data assets and analytics capabilities?
Key Components
Talent &
Skills
Does the organization have the right set of skills and capabilities along with a suitable talent model for retention and growth?
Key Components
Value
Creation
Does the organization effectively track value realized through analytics and how are those gains distributed in the value chain?
Key Components
The first pillar of our data maturity survey focuses on Strategy and Sponsorship. It gauges whether your organization has an established vision and support at the senior leadership level for analytics to have a strategic impact.
North Star and Vision
An organization’s North Star and Vision play a crucial role in defining the future of its data analytics capabilities. This subsection explores whether your organization has identified its guiding light and overarching goal in the realm of data analytics.
Data Strategy
Your Data Strategy forms the roadmap that your organization follows towards achieving its data vision. Here, we delve into how you plan to acquire, manage, use, and secure data in the long run.
Public Commitment
Public Commitment is an indicator of the priority an organization gives to its data analytics initiatives. It reflects the assurances made by your leadership about investing in and nurturing data analytics.
Track Record
Track Record offers insights into your organization’s past performance in implementing and benefiting from data analytics initiatives. It provides a glimpse of the successes and lessons learned in the data journey thus far.
The second pillar, Data Management, scrutinizes how formally your organization manages its data assets to maintain quality and enable effective use of analytics.
Organization
The Organization sub-component studies how your organization is structured to oversee data management. It evaluates the roles, responsibilities, and hierarchies in place to govern data use and security.
Process and Governance
Process and Governance ensure that your data assets are well-managed and used correctly and responsibly. This subsection delves into the rules, procedures, and controls established in your organization to govern data management.
Data Retention
Data Retention explores how your organization decides what data to retain, for how long, and under what conditions. It delves into the strategies you have in place for data archiving, disposal, and lifecycle management.
Data Quality
Data Quality underscores the accuracy, consistency, and reliability of your data. This sub-component evaluates the standards and procedures your organization employs to maintain high-quality data.
The third pillar, Technical Foundations, investigates whether your organization has a modern technology foundation underpinning its data assets and analytics capabilities.
Data Repositories
Data Repositories are the infrastructures where your organization’s data is stored and managed. This subsection focuses on the types of data repositories your organization uses, their robustness, and their suitability to your data needs.
Architecture
The Architecture sub-component delves into the design and structure of your data systems. It scrutinizes the interrelations between your data systems and the overall coherence of your data architecture.
Platforms
Platforms are the applications and tools your organization uses to process and analyze data. This subsection reviews the platforms you use, their appropriateness to your data goals, and their integration into your data infrastructure.
Data Catalogs
Data Catalogs are the organized inventories of your data assets. This sub-component looks into how your data is catalogued, its accessibility to users, and the ease of discovering and understanding data assets.
The fourth pillar, Talent and Skills, assesses whether your organization has the right set of skills and capabilities along with a suitable talent model for retention and growth.
Analytics Expertise
Analytics Expertise gauges the level of proficiency your team has in various data analytics tools and methodologies. This subsection assesses the technical prowess of your team and how it is used to derive valuable insights from data.
Resources’ Tenure
Resources’ Tenure looks at the stability and experience of your data team. It examines the longevity of your team members in their roles and how this affects your organization’s data capabilities.
Business Skills
Business Skills emphasize the knowledge your data team has about your industry and your business. This subsection focuses on your team’s ability to align data insights with business objectives and industry trends.
Learning Pathways
Learning Pathways assess the opportunities your organization provides for continual learning and skill improvement. It delves into the training programs, workshops, and courses available for your team to keep pace with evolving data trends.
The fifth and final pillar, Value Creation, probes if your organization effectively tracks value realized through analytics and how those gains are distributed in the value chain.
Value Tracking
Value Tracking delves into how your organization measures the benefits reaped from data analytics. This subsection investigates the metrics and indicators you use to quantify and track the value derived from data insights.
Funding Model
The Funding Model sub-component explores how your organization finances its data analytics initiatives. It assesses the models you employ to fund your data projects and how these models influence the value-creation process.
Financial Impact
Financial Impact examines the economic benefits that your data initiatives bring to your organization. This subsection scrutinizes the tangible and intangible financial impacts of your data projects.
Data Products
Data Products are the tangible outputs of your data initiatives. This sub-component studies the types of data products your organization creates, their usability, and their contribution to your overall value creation.
The journey to data maturity is not merely a theoretical exercise; it’s an imperative transformation that mirrors the broader shift in many industries toward a more data-driven and AI-enabled future. While the path may be complex, the rewards are undeniably substantial. By wholeheartedly embracing a comprehensive approach to data transformation, encapsulated within the framework of the five key pillars, companies are not only positioned to overcome their current challenges but also to pioneer the way forward in this new era of digital finance.
With this comprehensive assessment, your organization gains clarity and a deep understanding of your organization’s data maturity level and offers a roadmap for future improvements
Data is a critical asset in workload migrations to the cloud. Infinitive has proven business, technology, and process accelerators to expedite user adoption, save costs by reducing cycle times, and meet your business goals while your work is interrupted
As an AWS Advanced Consulting Partner, we understand migration needs are unique to each organization, and our proven and flexible framework will accommodate your unique business needs.
Strategy & Sponsorship
Does the organization have an established vision and sponsorship at the senior leadership level for analytics to have a strategic impact?
Key Components
Data Management
Does the organization formally manage it’s data assets to maintain quality and enable effective use in analytics?
Key Components
Technical Foundations
Does the organization have a modern technology foundation underpinning its data assets and analytics capabilities?
Key Components
Talent & Skills
Does the organization have the right set of skills and capabilities along with a suitable talent model for retention and growth?
Key Components
Value Creation
Does the organization effectively track value realized through analytics and how are those gains distributed in the value chain?
Key Components
Value Creation
Does the organization effectively track value realized through analytics and how are those gains distributed in the value chain?
Key Components
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