Digital transformation is no longer an option but an imperative for business survival. Companies that harness technologies like cloud, AI, IoT, and big data analytics will gain substantial competitive advantage.
The Accelerating Pace of Digital Disruption
Per IDC, by 2023 over 50% of global GDP will be digitized. Organizations without mature digital capabilities risk extinction. Consider these statistics:
- 63% of executives say digital maturity is required to stay competitive [1]
- 78% of leaders state COVID-19 has accelerated digital plans [2]
- 2025 projected ROI of digital investments is 2-3X today’s spend [3]
However, research shows 70% of ambitious digital transformations still fail due to poor planning and execution [4]. Following a structured approach is key to digitally maturing safely and efficiently.
This guide provides a comprehensive methodology for assessing and systematically improving an organization’s digital capabilities over time.
What Exactly is a Digital Maturity Model?
A digital maturity model evaluates an organization’s adoption and mastery of digital technologies to achieve business objectives. Like organizational development models, it establishes a progression of stages to represent increasing sophistication.
Assessing against standard criteria shows current strengths/weaknesses and guides priorities for advancing to next stage. Frameworks enable:
- Unified understanding of digital vision
- Objective evaluations relative to peers
- Data-driven roadmaps for phased modernization
- Metrics to monitor progress over multiyear programs
Maturity models quantify less tangible aspects of transformation like culture, leadership, innovation DNA and provide structure for the journey.
Common Digital Maturity Models
| Model | Focus |
|---|---|
| MIT Sloan Management Review | Overall organizational capabilities |
| Deloitte Digital Maturity | Customer engagement capabilities |
| TM Forum Digital Maturity | Telecom ecosystem transformation |
| HFS OneOffice | Integrating front, middle, back office |
| UC Berkeley DIG | Digital integrated into operations |
Stages of the Digital Maturity Journey
Maturity models contain a ladder of successive stages depicting increasing sophistication and integration of digital capabilities. While terminology differs, stages can be summarized as:
Stage 1: Initial
Manual or minimal automation. No enterprise-wide coordination. Low leadership prioritization.
Stage 2: Foundational
Functional digitization emerges. Isolated systems and data. Basic metrics and governance.
Stage 3: Defined
Standard digital processes documented. Expanding integration between systems/data. Centralized governance.
Stage 4: Quantitatively Managed
Integrated digital platforms. Extensive automation with cloud, IoT, AI. Security policies limit risk.
Stage 5: Optimizing
Organization wide utilization of emerging technology. Digital KPIs drive decisions. Focus on innovation.
The stages build over a 5+ year timeline guided by a comprehensive digital strategy. Companies should not rush target states but rather focus on sustainability.
Digital Maturity Assessment Methods
Measuring where your organization falls on the maturity continuum is crucial for planning and prioritizing enhancement efforts.
Self-Assessments
Structured self-assessments like McKinsey’s Digital Quotient survey executives and staff on 50+ benchmark practices across strategy, culture, organization, capabilities, governance, and infrastructure.
Weighting responses produces an overall score from 1 (Initial) to 5 (Optimizing) that ranks your digital maturity. Highly detailed, it identifies priority gaps to address.
External Assessments
Unbiased external maturity assessments conducted by management consultants add credibility for leaders seeking large digital transformation budgets.
Qualitative interviews and quantitative audits evaluate depth of digital tooling, data integration, automation, analytics usage, and skills. This produces a numeric maturity rating and roadmap.
Machine Learning-Enabled Assessments
Emerging solutions apply natural language processing, neural networks, and benchmark regression modeling to analyze documents, conduct employee surveys, mine system usage data and compute overall company maturity scores.
Besides efficiency, AI assessments provide predictive forecasts on maturation velocity to establish realistic targets. They also continuously rerun program data to reveal progress trajectory deviations needing correction.
Developing a Digital Maturity Improvement Roadmap
With current maturity baselined, CIOs/CTOs can chart a program to methodically enhance their organization’s digital capabilities over time.
8 Step Maturity Improvement Methodology
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Set Target Maturity Stage – Define forward-looking goal based on corporate objectives 3-5 years out
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Benchmark Capabilities – Audit/score current state across all dimensions of target stage
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Identify Gaps – Quantify differences between present vs. desired future abilities
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Digital Strategic Plan – Craft roadmap to close gaps through sequential initiatives over years
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Institute Governance – Standard policies, data/security frameworks to manage risk
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Launch Pilots – Start with lighthouse projects showing quick ROI wins
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Scale & Fund – Secure multi-year capital to accelerate rollouts through agile iteration
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Track & Monitor – Dashboards with digital KPIs, project status visibility to adjust in real-time
This structured approach aligns digital efforts to overarching corporate goals while allowing flexibility over longer time horizons.
For example, let’s examine a hypothetical retail organization:
Maturity Evaluation
- External auditor assessment score: 2.4 = Foundational capabilities
3 Year Roadmap
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Target Stage: 4.0 = Quantitatively Managed
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Strategic Initiatives: Customer cloud migration, supply chain analytics stack update, robotic process automation, staff digital academies
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Annual Benchmarks: Year 1 = 3.1 | Year 2 = 3.6 | Year 3 = 4.1
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Budget: $50M
Overcoming Resistance to Increase Maturity
While methodical in strategy, digital maturity programs require rapid execution. Leaders must overcome organizational resistance to transformational change. It demands new knowledge, new tools, new roles, and new processes fundamentally challenging institutional inertia.
If not managed carefully, 70% of ambitious efforts fall short of objectives due to poor change management.
Best practices include:
- Early communication of maturity vision from executives
- Cross-functional digital literacy training
- Retraining programs for those displaced by automation
- Culture nurturing innovation and tolerating fast failure
- Incentives for adopting modern behaviors and tools
- Matrixed project teams combining emerging talent + veterans
- Phased pilots limiting scope of initial changes
- Sandbox environments to practice new digital workflows
- Post-implementation support channels
- Redeploying savings from automation into digital skills investment
Tracking Digital Maturity Improvements
Gaining stakeholder support over multi-year modernization programs requires demonstrating tangible quick wins and sustained return on investment:
Sample Success Metrics
- Decreased system outages after upgrades
- Reduction in cyberattack vulnerabilities
- Increase in customer satisfaction score
- Higher digital workflow adoption across groups
- Upskilling rates or certifications achieved
- Faster case resolution via automation
- Rise in paperless transaction volumes
- Return on tech investments relative to market average
Building standardized dashboards, advanced analytics, and reporting around digital KPIs accelerates fact-based decision making and maturity benchmarking against peers. But targets should adapt based on business environment shifts.
Industry Perspectives on Digital Maturity
While maturity models provide frameworks, practical application must consider industry context. Tailoring based on external realities and constraints ensures achievable roadmaps.
Public Sector – Government agencies face constitutional barriers around privacy, security, budgets, and public transparency regulating the pace of digital modernization possible.
Financial Services – Banks and insurers require meticulous data governance, decentralized access controls, and system resiliency before undertaking ambitious technology transformations.
Healthcare – Strict safety regulations mean pharma/providers must take measured approaches when applying IoT, ML, and cloud to balance innovation with ethics, privacy, and reliability.
Regardless of industry, the principles of structured maturity benchmarking, gap analysis, and managed improvement planning hold true.
Final Recommendations
Here are best practices when leveraging digital maturity models:
- Obtain executive sponsorship early
- Assess honestly against external benchmarks
- Institute strong data security and governance guardrails
- Prioritize low risk high reward early deliverables
- Emphasize change management and new capability building
- Re-evaluate strategy frequently as markets evolve
Digital maturity lifts all boats – better performance, smarter decisions, happier customers. Using assessments models to shine a light on strengths and gaps ultimately makes companies healthier.
